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Traditionally, the quality of a multimedia system was mainly assessed through the evaluation of its Quality of Service (QoS) that is by evaluating system parameters such as bandwidth, latency, jitter, throughput, transmission delay, availability, etc. However, these metrics often failed to capture the actual end-user perceived quality, which has prompted the development of the construct of Quality of Experience (QoE), widely understood as an interaction of the technical features of multimedia systems with perceptual, and cognitive/emotional factors involved in the interpretation of those features by users. This chapter addresses the open issues in the field of QoS and QoE assessments. First, the perceptual characteristics of the multiview content are analyzed, and then a survey on the existing approaches for QoS and QoE estimation is performed. The analysis is then focused on the subjective aspects of QoE assessment, by describing the standard methodologies currently used and new trends based on human factors research. Finally, the chapter offers a few guidelines for future research directions in the field.

Immersive media, such as free view point video and 360° video, are expected to be dominant as broadcasting services. The light field (LF) imaging is being considered as a next generation imaging technology offering the possibility to provide new services, including six degree-of-freedom video. The drawback of this technology is in the size of the generated content thus requiring novel compression systems and the design of ad-hoc methodologies for evaluating the perceived quality. In this paper, the relation between depth map quality and overall quality of LF image is studied. Next, a reduced reference quality assessment metric for LF images is presented. To predict the quality of distorted LF images, the measure of distortion in the depth map is exploited. To test and validate the proposed framework, a subjective experiment has been performed, and a LF image quality dataset has been created. The dataset is also used for evaluating the performance of state-of-the-art quality metrics, when applied to LF images. The achieved results evidence that the estimated quality score by the proposed framework has a significant correlation with subjective quality rating. Consequently, reference data can be delivered to the clients thus allowing the local estimation of the perceived quality of service.

Recent years have witnessed a rapid growth of user generated videos thanks to the availability of affordable video recording devices and the extreme popularity of social media platforms. Accordingly, there is a challenge for designing highly efficient video quality assessment models to monitor, control, and optimize this content. In this contribution, a novel no-reference video quality metric for user generated video is presented. It exploits the spatial and temporal information contained in the center patch of video frames and a Support Vector Regressor system for computing the objective score. Experimental results show the effectiveness of the proposed approach. To promote reproducible research and public evaluation, an implementation of RM3VQA has been made available online: https://github.com/pramitmazumdar/RM3VQA.

Data-sets play a crucial role in advancing the research. However, getting access to real-world data becomes difficult when it comes to critical infrastructures and more so if that data is being acquired for security research. In this work, a comprehensive dataset from a real-world smart electric grid testbed is collected and shared with the research community. A few of the unique features of the dataset and testbed are highlighted.

The upcoming transport revolution is dramatically increasing the navigation integrity requirements. However, traditional techniques for increasing the integrity of the position information are usually based on the use of a high number of satellite signals. We propose to add an external integrity source based on the use of on-board visual sensors. Shift and rotation of the vehicle are estimated from the vanishing point of the road markings, and exploited to define a virtual track for its motion. The GNSS-only solution is then compared to the one constrained to the virtual track, and an integrity check is performed based on a threshold. The performed experiments prove the possibility of exploiting the visual system to reliably compute the vehicle’s dynamics from the acquired images, and show the impact of the virtual track constraint on the integrity check.

The objective of this work is to evaluate the feasibility of the integration of visual sensors in the framework of GNSS-based vehicle localization systems. Undoubtedly GNSS plays a key role in vehicle localization. However, the impact of GNSS faults (e.g. satellite and constellation failure), signal degradation (e.g. ionospheric scintillations, multipath) and external threats (e.g. jamming and spoofing) need to be taken into account. To address this issue, we propose a three-level localization framework based on the use of additional visual sensors. Thanks to the visual input, the inaccurate GNSS measurements are refined by tracking georeferenced landmarks to obtain the vehicle absolute position. Moreover, the same sensors can be used to obtain the relative position and motion of the vehicle. Every time a new group of landmarks is detected, it is possible to repeat the absolute positioning process to cancel the drift accumulated by the relative localization procedure. This work represents the first step towards the realization of the proposed localization technique. Initial testing to evaluate its suitability has been carried out and is reported hereafter.

Light field imaging is increasingly spreading and its applications are reaching a larger number of users. The quality of the rendered content as perceived by the viewers is a key factor for the future development of this technology. Many factors can cause a degradation of the Light Field quality, from data acquisition/creation to the final rendering. To increase the perceived quality of the Light Field content, as usually performed for 2D and 3D content, processing techniques can be applied. In this work, an approach for enhancing Light Field videos is presented. The proposed approach is based on the characteristics of the human visual system and relies on the estimation of depth, motion and saliency. Those features guide a selective enhancement that is implemented in the Laguerre-Gauss Transform domain. The performed tests show the effectiveness of the proposed method.

Industrial and Automation Control systems traditionally achieved security thanks to the use of proprietary protocols and isolation from the telecommunication networks. Nowadays, the advent of the Industrial Internet of Things poses new security challenges. In this paper, we first highlight the main security challenges that advocate for new risk assessment and security strategies. To this end, we propose a security framework and advanced tools to properly manage vulnerabilities, and to timely react to the threats. The proposed architecture fills the gap between computer science and control theoretic approaches. The physical layers connected to Industrial Control Systems are prone to disrupt when facing cyber-attacks. Considering the modules of the proposed architecture, we focus on the development of a practical framework to compare information about physical faults and cyber-attacks. This strategy is implemented in the ATENA architecture that has been designed as an innovative solution for the protection of critical assets.

The assessment of Quality of Experience (QoE) for stereoscopic 3-D video is a challenging task, especially in 3-D video compression and transmission applications. The focus of this contribution is the development of a QoE assessment framework, in line with the latest standardization progress in the field of QoE assessment, for understanding the visual effect of asymmetric and symmetric encoding for immersive media. Asymmetric stereoscopic video coding exploits the binocular suppression of the human vision system by representing one of the two views with a lower quality. This processing, while of limited effects on image quality, may influence the overall QoE. Many studies show that the QoE of immersive media such as 3-DTV can be thought as the combination of the perceived visual quality, the perceived depth quality, the visual fatigue, and visual discomfort. In this paper, we aim at: 1) exploiting the concept of preference of experience and protocols recently standardized for characterizing QoE; 2) conducting a case study using these standardized protocols to investigate the factors involving visual discomfort in stereoscopic video sequences with a focus on binocular rivalry; and 3) presenting the results of subjective experiments performed, by using the perceptual quality and preference of experience assessment protocols, for evaluating the impact of symmetrical, asymmetrical, and alternate coding schemes.

Omni-directional imaging records the visual information from any direction with respect to a given view-point. It is gaining consumers’ popularity due to fast spreading of low-cost devices both for acquisition and rendering. The possibility to render the whole surrounding space represents a further step towards immersivity, thus providing the user with the illusion of physically being in a virtual environment. The understanding of visual attention mechanisms for these images is a relevant topic for processing, coding, and exploiting such data. In this contribution, a saliency model for omni-directional images is presented. It is based on the combination of low-level and semantic features. The first ones account for texture, viewport saliency, hue and saturation, while the second are used to take into account the impact of the presence of human subjects on the saliency. The proposed model has been tested in the “Salient360! Visual attention modeling for 360°View the MathML sourceImages” Grand Challenge. The model, the achieved results, and finding/discussions are here presented.

The Internet of Things paradigm improves the classical information sharing scheme. However, it has increased the need for granting the security of the connected systems. In the industrial field, the problem becomes more complex due to the need of protecting a large attack surface while granting the availability of the system and the real time response to the presence of threats. In this contribution, we deal with the injection of tampered data into the communication channel to affect the physical system. The proposed approach relies on designing a secure control system by coding the output matrices according to a secret pattern. This pattern is created by using the Fibonacci p-sequences, numeric sequence depending on a key. The proposed method is validated on the Hydra testbed, emulating the industrial control network of a water distribution system.

Depth-Image-Based-Rendering (DIBR) techniques are essential for three-dimensional (3D) video applications such as 3D Television (3DTV) and Free-Viewpoint Video. However, this process is based on 3D warping and can induce serious distortions whose impact on the perceived quality is far different from the one experienced in the 2D imaging processes. Since quality evaluation of DIBR-synthesized views is fundamental for the design of perceptually friendly 3D video systems, an appropriate objective quality metric targeting the assessment of DIBR-synthesized views is momentous. Most of the 2D objective quality metrics fail in assessing the visual quality of DIBR-synthesized views because they have not been conceived for addressing the specificities of DIBR-related distortions. In this paper, a new full-reference objective quality metric, 3DSwIM (3D Synthesized view Image Quality Metric), dedicated to artifacts detection in DIBR-synthesized view-points is presented. The proposed scheme relies on a comparison of statistical features of wavelet subbands of two input images: the original image and the DIBR-based synthesized image. A registration step is included before the comparison step so that best matching blocks are always compared to ensure "shifting-resilience". In addition, a skin detection step weights the final quality score in order to penalize distorted blocks containing "skin-pixels" based on the assumption that a human observer is most sensitive to impairments affecting human subjects. Experimental tests show that the proposed method outperforms the conventional 2D and DIBR-dedicated quality metrics under test. HighlightsThis paper presents a new full- reference objective quality metric dedicated to artifacts detection in 3D synthesized views.The proposed metric is based on the comparison of statistical features of wavelet subbands of the original image and the DIBR-based synthesized image."Shifting-resilience" is granted by the use of a registration algorithm.The final quality score is weighted depending on the presence of "skin-pixels" based on the assumption that a human observer is more sensitive to impairments affecting human subjects.Experimental tests show that the proposed method outperforms the 2D conventional and DIBR-synthesized views dedicated quality metrics under test.

The security of Cyber Physical Systems is a key factor since these architectures are being applied in many critical scenarios, such as power or water plants, hospitals, etc. In the state of the art, several approaches have been proposed to deal with the possible attacks that could be inferred to the Cyber Physical Systems. This contribution proposes a method for counter fighting the injection of tampered data in the communication channel. If this attack is not timely detected, it may result in severe disruption of the system or even in its complete damage. The proposed approach is based on coding the physical output of the system through permutation matrices whose scheme varies based on a randomly generated sequence. The strength of this method is in reducing the possibility of a successful injection attack while limiting the computational complexity. The experimental tests prove the effectiveness of the proposed scheme in detecting the performed attack while granting the real time constraints of the Cyber Physical Systems.

Light Field imaging derives from the fundamentals of light field sampling, where the spatial information about a scene can be captured with angular information. That is, the Light Field imaging is based on a camera recording information about the intensity of light from the scene and about the direction of the light rays. The acquired data can be shown to the user in different ways, such as image with digitally extended depth of field, 3D, parallax, and 360 degree display. In this contribution, the impact of different rendering techniques on the Quality of Experience is addressed. The achieved results show that the visualization techniques may have different impact on the perceived quality even when the same content is considered.

In free-viewpoint rendering systems, one of the most challenging goals is the creation of virtual views based on available color texture (RGB) and depth data. Conventional depth-image-based rendering (DIBR) approaches have assumed that the virtual camera can only be displaced horizontally, thus leading to fairly simple disocclusion artifacts. However, in free-viewpoint DIBR, the virtual camera can be positioned in an arbitrary way and the respective disocclusion artifacts can exhibit complicated anisotropic appearances. Consequently, conventional approaches for compensating disocclusion holes usually fail in such arbitrary camera motion. We present a disocclusion compensation technique based on texture inpainting. We propose a layered representation of both the color and depth images in local foreground, background, and undefined segments (a trimap). This representation allows for employing an efficient alpha-matting approach for reconstructing the underlying opacity layer followed by a background compensation and layered rendering. The performance of the proposed method is evaluated with respect to the state-of-the-art through objective and subjective tests. The achieved results, especially for large camera displacements, outperform the state-of-the-art. Those results assess the effectiveness of the proposed method and highlight the need for new quality metrics able to address the impairments of this type of content.

This paper presents the results of the depth estimation challenge for dense light fields, which took place at the second workshop on Light Fields for Computer Vision (LF4CV) in conjunction with CVPR 2017. The challenge consisted of submission to a recent benchmark [7], which allows a thorough performance analysis. While individual results are readily available on the benchmark web page http://www.lightfield-analysis.net, we take this opportunity to give a detailed overview of the current participants. Based on the algorithms submitted to our challenge, we develop a taxonomy of light field disparity estimation algorithms and give a report on the current state-ofthe- art. In addition, we include more comparative metrics, and discuss the relative strengths and weaknesses of the algorithms. Thus, we obtain a snapshot of where light field algorithm development stands at the moment and identify aspects with potential for further improvement.

Evaluation of perceived quality of light field images, as well as testing new processing tools, or even assessing the effectiveness of objective quality metrics, relies on the availability of test dataset and corresponding quality ratings. This paper presents SMART light field image quality dataset. The dataset consists of source images (raw data without optical corrections), compressed images, and annotated subjective quality scores. Furthermore, analysis of perceptual effects of compression on SMART dataset is presented. Next, the impact of image content on the perceived quality is studied with the help of image quality attributes. Finally, the performances of 2-D image quality metrics when applied to light field images are analyzed.

In this work, the problem of dynamic video scene creation obtained by combining information extracted from multiple video sequences is considered. The main novelty of the proposed approach relies on the use of aesthetic features for automatically aggregating the inputs from different cameras in a unique video. While prior methodologies have separately addressed the issues of aesthetic feature extraction from videos and video orchestration, in this work we exploit selected features of a scene for automatically selecting the shots being characterized by the best aesthetic score. In order to evaluate the effectiveness of the proposed method, a subjective experiment has been carried out with experts from the audiovisual field. The achieved results are encouraging and show that there is space for improving the performances.

The spreading of low-cost and easy-to-implement systems for Virtual Reality, make it possible for a large number of consumers to experience this technology. The application fields span a wide range and recently the educational aspect started having a significant impact. In this paper we design a framework that allows the user to visit a virtual museum in which all canvases painted by Caravaggio and conserved in Rome are displayed. The aim of this project is two-fold: on one hand we provide the user with the possibility of having a personalized and educative exploration of an artistic content, while on the other hand we assess the acceptability of this virtual reality-based application by the final user. The system has been implemented in three different versions, one based on a standard interaction between subject and PC, while the other two rely on the use of Google Cardboard, a low-cost framework for virtual reality rendering. In order to assess the Quality of Experience of the users of the system, we performed subjective experiments that showed pros and cons of the proposed system and highlighted some guidelines towards the use of VR for serious gaming. The synergic cooperation between Art History and ICT gave to this project a peculiar aim in which both disciplines' interests and needs are profitably combined to build a Digital Humanities project. The result is a product, which is philologically accurate and at the same time innovative in terms of technologies used.

In this work, the problem of video orchestration performed by combining information extracted by multiple video sequences is considered. The novelty of the proposed approach relies on the use of aesthetic features and of cinematographic composition rules for automatically aggregating the inputs from different cameras in a unique video. While prior methodologies have separately addressed the issues of aesthetic feature extraction from videos and video orchestration, in this work we exploit a set of features of a scene for automatically selecting the shots being characterized by the best aesthetic score. In order to evaluate the effectiveness of the proposed method, a preliminary subjective experiment has been carried out with experts from the audiovisual field. The achieved results are encouraging and show that there is space for improving the performances.

The robust design and adaptation of multimedia networks relies on the study of the influence of potential network impairments on the perceived quality. Video quality may be affected by network impairments, such as delay, jitter, packet loss, and bandwidth, and the perceptual impact of these impairments may vary according to the video content. The effects of packet loss and encoding artifacts on the perceived quality have been widely addressed in the literature. However, the relationship between video content and network impairments on the perceived video quality has not been deeply investigated. A detailed analysis of ReTRiEVED test video dataset, designed by considering a set of potential network impairments, is presented, and the effects of transmission impairments on perceived quality are analyzed. Furthermore, the impact on the perceived quality of the video content in the presence of transmission impairments is studied by using video content descriptors. Finally, the performances of well-known quality metrics are tested on the proposed dataset.

Light field technology may have a positive impact on several multimedia applications thanks to novel ways to explore the captured scenes, such as changing the parallax (horizontally and vertically) and refocusing the content. These innovative use cases require new considerations that affect the whole processing chain, from content acquisition to visualization, as well as the methodologies for quality evaluation. In particular, capturing and selecting the appropriate content is crucial for a successful development and evaluation of audiovisual technologies. Thus, this paper presents a framework addressing the reconsideration of the space of attributes for an adequate characterization of light field data. Firstly, an exhaustive characterization of light field content is described, based on various particular features, including depth and refocusing properties to traditional spatial, temporal, and color indicators. Then, based on this characterization, specific techniques are proposed for an effective selection of light field content for perceptual quality assessment.

In this paper, two image quality metrics based on morphological multiscale decompositions have been applied for the evaluation of free viewpoint video sequences. These sequences are synthesized using decompressed depth maps in the Depth-Image-Based Rendering synthesis process. Since the synthesis introduces edge distortion in the synthesized image/video, morphological filters are used for their ability to maintain important geometric information (i.e., edges) across different resolution levels. The edges displacement in different resolution scales is evaluated by means of the Mean Square Error. The adopted metrics show higher correlation with human judgment than state-of-the-art image quality measures used in this context.

The analysis of the impact of video content and transmission impairments on Quality of Experience (QoE) is a relevant topic for the robust design and adaptation of multimedia infrastructures, services, and applications. The goal of this paper is to study the impact of video content on QoE for different levels of impairments. In more details, this contribution aims at i) the study of the impact of delay, jitter, packet loss, and bandwidth on QoE, ii) the analysis of the impact of video content on QoE, and iii) the evaluation of the relationship between content related parameters (spatial-temporal perceptual information, motion, and data rate) and the QoE for different levels of impairments.

The knowledge of the user Quality of Experience (QoE) of the accessed services is of crucial importance for the robust design and adaptation of multimedia streaming networks. In this article, a video QoE estimation metric for video streaming services is presented. The proposed metric does not require information on the original video or the impairments affecting the communication channels. Results show that the proposed method can efficiently estimate the video QoE.

In this contribution, the design of a Light Field image dataset is presented. It can be useful for design, testing, and benchmarking Light Field image processing algorithms. As first step, image content selection criteria have been defined based on selected image quality key-attributes, i.e. spatial information, colorfulness, texture key features, depth of field, etc. Next, image scenes have been selected and captured by using the Lytro Illum Light Field camera. Performed analysis shows that the proposed set of images is sufficient for addressing a wide range of attributes relevant for assessing Light Field image quality.

Securing multimedia data from undesired manipulation is a widely investigated topic in the state of the art. A large number of techniques has been developed for protecting images, videos, and also audio from malicious attacks. Nowadays new imaging systems pose new challenges from the data protection point of view. In particular, plenoptic cameras allow to record multiple views of a scene by using a single camera in a single shot, thus avoiding the problems related to calibration and camera synchronization. In this contribution, a novel embedding scheme tuned to light fields is presented. The watermark is inserted in the horizontal and vertical detail subbands of the first level of the Haar wavelet transform. The aim of this work is twofold: the design of a water-marking system that does not affect the depth map estimation procedure and therefore the refocusing procedure and the 3D scene reconstruction. On the other hand, the impact of light field data modification with respect to the perceived quality has been investigated. Experimental tests, both objective and subjective, have been carried out for assessing the performances of the proposed algorithm.

Face processing techniques for automatic recognition in broadcast video attract the research interest because of its value in applications, such as video indexing, retrieval, and summarization. In multimedia press review, the automatic annotation of broadcasting news programs is a challenging task because people can appear with large appearance variations such as hair styles, illumination conditions and poses that make the comparison between similar faces more difficult. In this paper a technique for automatic face identification in TV broadcasting programs based on a gallery of faces downloaded from Web is proposed. The approach is based on a joint use of Scale Invariant Feature Transform descriptor and Eigenfaces-based algorithms and it has been tested on video sequences using a database of images acquired starting from a web search. Experimental results show that the joint use of these two approaches improves the recognition rate in case of use Standard Definition (SD) and High Definition (HD) standards.

The use of 3D video is growing in several fields such as entertainment, military simulations, medical applications. However, the process of recording, transmitting, and processing 3D video is prone to errors thus producing artifacts that may affect the perceived quality. Nowadays a challenging task is the definition of a new metric able to predict the perceived quality with low computational complexity in order to be used in real-time applications. The research in this field is very active due to the complexity of the analysis of the influence of stereoscopic cues. In this paper we present a novel stereoscopic metric based on the combination of relevant features able to predict the subjective quality rating in a more accurate way. acceptedVersion

No-reference video quality assessment is a challenging task since the quality evaluation is not based on a priori knowledge of the original signal. In this paper we propose a no-reference quality metric for IP-based video transmission. The video quality is estimated based on the evaluation of the artifacts introduced by H.264/AVC coding and by the impairments caused by the IP transmission system. Performance experiments show the effectiveness of the proposed system in matching the subjective judgment. The collected scores have been compared with state of art video quality metrics.

In this article the effects of video content on Quality of Experience (QoE) have been presented. Delivery of the video content with high level of QoE from bandwidth-limited and error-prone network is of crucial importance for the service providers. Therefore, it is of fundamental importance to analyse the impact of the network impairments and video content on perceived quality during the QoE metric design. The major contributions of the article are in the study of i)the impact of network impairments together with video content, ii) impact of the video content and ii) the impact of video content related parameters: spatial-temporal perceptual information, video content, and frame size on QoE has been presented. The results show that when the impact of impairments on perceived quality is low, the quality is significantly influenced by video content, and video content itself also has a significant impact on QoE. Finally, the results strengthen the need for new parameter characterization, for better QoE metric design.

This paper describes the design and first prototype implementation of an innovative concept of augmented instruments. The main idea is given by the opportunity offered by cameras and image recognition algorithms, to avoid the use of intrusive and often wired sensors. This latter aspect is indeed one of the main limitations to augmentation since also interested players usually try to avoid “external elements” on their priceless instruments.

This paper describes a recently created image database, TID2013, intended for evaluation of full-reference visual quality assessment metrics. With respect to TID2008, the new database contains a larger number (3000) of test images obtained from 25 reference images, 24 types of distortions for each reference image, and 5 levels for each type of distortion. Motivations for introducing 7 new types of distortions and one additional level of distortions are given; examples of distorted images are presented. Mean opinion scores (MOS) for the new database have been collected by performing 985 subjective experiments with volunteers (observers) from five countries (Finland, France, Italy, Ukraine, and USA). The availability of MOS allows the use of the designed database as a fundamental tool for assessing the effectiveness of visual quality. Furthermore, existing visual quality metrics have been tested with the proposed database and the collected results have been analyzed using rank order correlation coefficients between MOS and considered metrics. These correlation indices have been obtained both considering the full set of distorted images and specific image subsets, for highlighting advantages and drawbacks of existing, state of the art, quality metrics. Approaches to thorough performance analysis for a given metric are presented to detect practical situations or distortion types for which this metric is not adequate enough to human perception. The created image database and the collected MOS values are freely available for downloading and utilization for scientific purposes. We have created a new large database.This database contains larger number of distorted images and distortion types.MOS values for all images are obtained and provided.Analysis of correlation between MOS and a wide set of existing metrics is carried out.Methodology for determining drawbacks of existing visual quality metrics is described.

In this contribution the design of a bi-technological enhanced terminal for secure mobile communication is presented. It is based on the TETRA and TETRAPOL communication networks, that are currently used by public and private bodies as network infrastructures and are particularly exploited in case of emergency. The proposed system allows the use of both, TETRA and TETRAPOL, low level communications layers. Furthermore, the proposed terminal introduces high level capabilities that enhance the basic functionalities of these communication systems, while preserving the intrinsics security of the standards. The implementation of the proposed terminal architecture is the basis for the development of an integrated European network where emergency services and first responders share communications, processes, and a legal framework, to be used in case of natural disasters and security threats. In this contribution, the terminal architecture and the security analysis are introduced and discussed.

In this paper a video database, ReTRiEVED, to be used in evaluating the performances of video quality metrics is presented. The database contains 184 distorted videos obtained from eight videos of different content. Packet loss rate, jitter, delay, and throughput have been considered as possible distortions resulting from video transmission. Video sequences, collected subjective scores, and results of the performed analysis are made publicly available for the research community, for designing, testing and comparing objective video quality metrics. The analysis of the results shows that packet loss rate, throughput/bandwidth, and jitter have significant effect on perceived quality, while an initial delay does not significantly affect the perceived quality.

Internet of Things (IoT) refers to the capability to connect, communicate and remotely manage a large number of networked, automated devices via the Internet. IoT is becoming as part of daily life and aims to extend pervasive communication and networking anytime, anywhere with any device. In this context security requirements and architectures must be properly formulated, implemented in order to enforce the security policies during their life-cycle. This paper provides a survey and analysis of security in the area of IoT introducing an approach addressed to overcome the conventional security solutions and deploy a federated architecture for dynamic prevention, detection, diagnosis, isolation, and countermeasures against cyber attacks. Based on the analysis of the most common web services, the paper defines the security needs proposing a federated model to design an architecture for secure exchange of services in IoT paradigm.

The automatic labeling of faces in TV broadcasting is still a challenging problem. The high variability in view points, facial expressions, general appearance, and lighting conditions, as well as occlusions, rapid shot changes, and camera motions, produce significant variations in image appearance. The application of automatic tools for face recognition is not yet fully established and the human intervention is needed. In this paper, we deal with the automatic face recognition in TV broadcasting programs. The target of the proposed method is to identify the presence of a specific person in a video by means of a set of images downloaded from Web using a specific search key.

Automatic annotation of broadcasting news programs is a challenging task for multimedia press review. Usually in a video stream, the head of a person moves continuously and changes in facial expressions, lighting conditions, and camera motion produce significant distortions in the image appearance that can largely affect recognition performances. In this paper a system for automatic face identification in TV broadcasting programs is proposed. The proposed approach is based on a joint use of Scale Invariant Feature Transform descriptor and Eigenfaces-based approach. The algorithm has been tested on two national broadcasting channels. Experimental results show that the joint use of these two approaches improves the recognition rate.

In this work an analysis of the influence of contrast modification on people’s opinion is performed. Based on a previous study of the impact of image contrast modifications on human feelings, here we address the problem of determining the impact of the image contrast change on the opinion of a person. This analysis is based on subjective tests that have been performed exploiting crowdsourcing. The obtained results show a good correlation with the previous work and they witness the possibility to influence subjective opinion by means of contrast modification. This study can results in forensics tools for blind detection of opinion biasing by means of image processing.

Scale Invariant Feature Transform (SIFT) has been widely employed in several image application domains, including Image Forensics (e.g. detection of copy-move forgery or near duplicates). Recently, a number of methods allowing to remove SIFT keypoints from an original image have been devised studying the problem of SIFT security against malicious procedures. Such techniques are quite effective in producing an attacked image with very few (or no) keypoints, but at the expense of an image distortion. Final perceptual quality has been taken in account very roughly so far. In this paper, effectiveness of the attacking methods is evaluated also from the side of perceptual image quality; a new version of a SIFT keypoint removal method, based on a perceptual metric, is presented and an extended series of perceptive experiments is reported.

International audience; In this paper we present a novel image quality assessment technique for evaluating virtual synthesized views in the context of multi-view video.In particular, Free Viewpoint Videos are generated from uncompressed color views and their compressed associated depth maps by means of the View Synthesis Reference Software, provided by MPEG. Prior to the synthesis step, the original depth maps are encoded with different coding algorithms thus leading to the creation of additional artifacts in the synthesized views. The core of proposed wavelet-based metric is in the registration procedure performed to align the synthesized view and the original one, and in the skin detection that has been applied considering that the same distortion is more annoying if visible on human subjects rather than on other parts of the scene. The effectiveness of the metric is evaluated by analyzing the correlation of the scores obtained with the proposed metric with Mean Opinion Scores collected by means of subjective tests. These results are also compared against those of well known objective quality metrics. The experimental results confirm the effectiveness of the proposed metric.

Person re-identification through a camera network deals with finding a correct link between consecutive observations of the same target among different cameras in order to choose the most probable correspondence among a set of possible matches. This task is particularly challenging in presence of low-resolution camera networks. In this work, a method for people re-identification in a framework of low-resolution camera network is presented. The proposed approach can be divided in two parts. First, the illumination changes of a target while crossing the network is analyzed. The color structure is evaluated using a novel color descriptor, the Color Structure Descriptor, which describes the differences of dominant colors between two regions of interest. Afterwards, a new pruning system for the links, the Target Color Structure is proposed. Results shows that the improvements achieved applying Target Color Structure control are up to 4% for the top rank and up to 16% considering the first eleven more similar candidates. © 2013 SPIE-ISandT.

The aim of this work is the design of a novel audio watermarking technique based on the Linear Predictive Coding approach and on the psychoacoustic model defined in the MPEG-I standard. The embedding imperceptibility is achieved by exploiting the frequency masking effect. The evaluation of the perceived audio quality is performed by means of the standardized ITU-R BS.1387 quality assessment method. The effectiveness of the proposed method is tested in presence of attacks. © 2013 IEEE.

"The use of ear information for people identification has been under testing at least for 100 years. However, it is still an open issue if the ears can be considered unique or unique enough to be used as biometric feature. In this paper a biometric system for human identification based on ear recognition is presented. The ear is modeled as a set of contours extracted from the ear image with an edge potential function. The matching algorithm has been tested in presence of several image modifications. Two human ear databases have been used for the tests. The experimental results show the effectiveness of the proposed scheme."

In this paper a methodology for digital image forgery detection by means of an unconventional use of image quality assessment is addressed. In particular, the presence of differences in quality degradations impairing the images is adopted to reveal the mixture of different source patches. The ratio behind this work is in the hypothesis that any image may be affected by artifacts, visible or not, caused by the processing steps: acquisition (i.e., lens distortion, acquisition sensors imperfections, analog to digital conversion, single sensor to color pattern interpolation), processing (i.e., quantization, storing, jpeg compression, sharpening, deblurring, enhancement), and rendering (i.e., image decoding, color/size adjustment). These defects are generally spatially localized and their strength strictly depends on the content. For these reasons they can be considered as a fingerprint of each digital image. The proposed approach relies on a combination of image quality assessment systems. The adopted no-reference metric does not require any information about the original image, thus allowing an efficient and stand-alone blind system for image forgery detection. The experimental results show the effectiveness of the proposed scheme.

In this paper we propose a new hybrid architecture between client/server and P2P network architectures in order to provide better service quality to the end-user. To distribute and protect the content, we use a discrete geometry tool as the Finite Radon Transform (FRT) in a Maximum Distance Separable (MDS) fashion. The presented results clarify the interest of the proposed architecture in terms of QoS.

'View plus depth' is an attractive compact representation format for 3D video compression and transmission. It combines 2D video with depth map sequence aligned in a per-pixel manner to represent the moving 3D scene in interest. Any different-perspective view can be synthesized out if this representation through Depth-Image Based Rendering (DIBR). However, such rendering is prone to disocclusion errors: regions originally covered by foreground objects become visible in the synthesized view and have to be filled with perceptually-meaningful data. In this work, a technique for reducing the perceived artifacts by inpainting the disoccluded areas is proposed. Based on Criminisi's exemplar-based inpainting algorithm, the developed technique recovers the disoccluded areas by using pixels of similar blocks surrounding it. In the original work, a moving window is centered on the boundaries between known and unknown parts ('target window'). The known pixels are used to select windows which are most similar to the target one. When this process is completed, the unknown region of the target patch is filled with a weighted combination of pixels from the selected windows. In the proposed scheme, the priority map, which defines the rule for selecting the order of pixels to be filled, has been modified to meet the requirement for disocclusion hole filling and a better non-local mean estimate has been suggested accordingly. Furthermore, the search for similar patches has also been extended to previous and following frames of the video under processing, thus improving both computational e±ciency and resulting quality. The effectiveness of the proposed method is demonstrated by objective and subjective tests.

The use of digital media for improving the effectiveness of teaching methodologies in Universities is increasing. In this contribution the experience performed at University of Roma TRE is presented. Since 2005 an online contest is used in the Multimedia class for improving both knowledge and human interaction. This paper shows the competitive-collaborative learning scheme adopted and it reports the feedback received by the students that has been collected by means of a questionnaire. The obtained comments show the effectiveness of the proposed learning scheme.

The increasing use of digital image-based applications is resulting in huge databases that are often difficult to use and prone to misuse and privacy concerns. These issues are especially crucial in medical applications. The most commonly adopted solution is the encryption of both the image and the patient data in separate files that are then linked. This practice results to be inefficient since, in order to retrieve patient data or analysis details, it is necessary to decrypt both files. In this contribution, an alternative solution for secure medical image annotation is presented. The proposed framework is based on the joint use of a key-dependent wavelet transform, the Integer Fibonacci-Haar transform, of a secure cryptographic scheme, and of a reversible watermarking scheme. The system allows: i) the insertion of the patient data into the encrypted image without requiring the knowledge of the original image, ii) the encryption of annotated images without causing loss in the embedded information, and iii) due to the complete reversibility of the process, it allows recovering the original image after the mark removal. Experimental results show the effectiveness of the proposed scheme.

In this contribution, an evaluation of the effectiveness of Application Layer-Forward Error Correction (AL-FEC) scheme in video communications over unreliable channels is presented. In literature, several AL-FEC techniques for reducing the effect of noisy transmission on multimedia communication have been adopted. Recently, their use has been proposed for inclusion in TV over IP broadcasting international standards. The objective of the analysis performed in this paper is to verify the effectiveness of AL-FEC techniques in terms of perceived Quality of Service (QoS) and more in general of Quality of Experience (QoE), and to evaluate the trade-off between AL-FEC redundancy and video quality degradation for a given packet loss ratio. To this goal, several channel error models are investigated (random i.i.d. losses, burst losses, and network congestions) on test sequences encoded at 2 and 4 Mbps. The perceived quality is evaluated by means of three quality metrics: the full-reference objective quality metric NTIA-VQM combined with the ITU-T Rec. G.1070, the full-reference DMOS-KPN metric, and the pixel-wise error comparison performed by using the PSNR distortion measure. A post-processing synchronization between the original and the reconstructed stream has also been designed for improving the fidelity of the performed quality measures. The experimental results show the effectiveness and the limits of the Application Layer protection schemes. © 2011 Battisti et al; licensee Springer.