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A three-dimensional (3D) video is a special video representation with an artificial stereoscopic vision effect that increases the depth perception of the viewers. The quality of a 3D video is generally measured based on the similarity to stereoscopic vision obtained with the human vision system (HVS). The reason for the usage of these high-cost and time-consuming subjective tests is due to the lack of an objective video Quality of Experience (QoE) evaluation method that models the HVS. In this paper, we propose a hybrid 3D-video QoE evaluation method based on spatial resolution associated with depth cues (i.e., motion information, blurriness, retinal-image size, and convergence). The proposed method successfully models the HVS by considering the 3D video parameters that directly affect depth perception, which is the most important element of stereoscopic vision. Experimental results show that the measurement of the 3D-video QoE by the proposed hybrid method outperforms the widely used existing methods. It is also found that the proposed method has a high correlation with the HVS. Consequently, the results suggest that the proposed hybrid method can be conveniently utilized for the 3D-video QoE evaluation, especially in real-time applications. [ABSTRACT FROM AUTHOR]

The transport sector is experiencing a fast and revolutionary development, moving toward the deployment of autonomous vehicles. Thus, the accuracy of the position information and the integrity of the navigation system have become key factors. In this article, we address the problem of the enhancement of the integrity of the position provided by a global navigation satellite system receiver by exploiting sensor fusion. To this aim, we estimate the lateral offset and heading of the vehicle with respect to a georeferenced roadway centerline from the images supplied by an on-board camera. Moreover, we perform integrity monitoring based on the implementation of the solution separation in the parity space. The numerical results indicate that the use of sensor fusion and digital map allows us to attain a longitudinal protection level reduction with respect to the case in which sensor fusion is not exploited. More specifically, a decrease of about 70% is achieved when a single constellation is used, while reduction is less relevant, about 15%, when two constellations are employed. [ABSTRACT FROM AUTHOR]

Over the last few years applications based on the use of immersive environments, where physical and digital objects coexist and interact, have gained widespread attention. Thanks to the development of new visualization devices, even at low cost, and increasingly effective rendering and processing techniques, these applications are reaching a growing number of users. While the adoption of digital information makes it possible to provide immersive experiences in a number of different applications, there are still many unexplored aspects. In this work, a preliminary step to understand the impact of the scene content on human perception of the virtual 3D elements in a mixed reality has been performed. To this aim, a subjective test was designed and implemented to collect the reaction time of a set of users in a mixed reality application. In this test each user was asked to wear an augmented reality headset and to catch a virtual objects randomly appearing in the subject’s field of view. We first estimated the detection accuracy through omitted, anticipated, and completed responses; then we related stimulus location, scene content and estimated accuracy. For this purpose, the area of stimulus presentation was divided into upper, lower, right, left, inner, and outer, to understand in which area responses were omitted and anticipated with respect to the central point of view. Experimental results show that, in addition to the saliency of the real scene, natural body gesture technology and limited field of view influenced human reaction time. [ABSTRACT FROM AUTHOR]

Abstract 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.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Low-cost personal computers, wireless access technologies, the Internet, and computer-equipped classrooms allow the design of novel and complementary methodologies for teaching digital information security in electrical engineering curricula. The challenges of the current digital information era require experts who are effectively able to counteract piracy, forgery, copyright infringement, and so on. Digital watermarking is one possible technique for fighting piracy, which consists of the insertion of invisible but robust information to protect the data. In this paper, a new teaching approach, designed for testing student skills and progressing in multimedia data protection, is presented. This consists of a distributed security game where students compete by first using the developed watermarking techniques and then attacking each other's methods, thus verifying their robustness. Groups of students from different universities and countries play against each other, trying to compromise other teams' hiding systems while protecting their own data from attacks. The proposed methodology can be considered as an appealing approach for stimulating learning, cooperation, and team competition. The effectiveness of the teaching method is verified by a student survey and their academic results. [ABSTRACT FROM AUTHOR]

In this paper, we introduced and tested a new system based on a sensorized seat, to evaluate the sitting dynamics and sway alterations caused by different cognitive engagement conditions. An office chair was equipped with load cells, and a digital and software interface was developed to extract the Center of Pressure (COP). A population of volunteers was recruited to evaluate alterations to their seated posture when undergoing a test specifically designed to increase the cognitive engagement and the level of stress. Relevant parameters of postural sway were extracted from the COP data, and significant alterations were found in all of them, highlighting the ability of the system to capture the emergence of a different dynamic behavior in postural control when increasing the complexity of the cognitive engagement. The presented system can thus be used as a valid and reliable instrument to monitor the postural patterns of subjects involved in tasks performed in a seated posture, and this may prove useful for a variety of applications, including those associated with improving the quality of working conditions. [ABSTRACT FROM AUTHOR]

Omnidirectional, or 360°, cameras are able to capture the surrounding space, thus providing an immersive experience when the acquired data is viewed using head mounted displays. Such an immersive experience inherently generates an illusion of being in a virtual environment. The popularity of 360° media has been growing in recent years. However, due to the large amount of data, processing and transmission pose several challenges. To this aim, efforts are being devoted to the identification of regions that can be used for compressing 360° images while guaranteeing the immersive feeling. In this contribution, we present a saliency estimation model that considers the spherical properties of the images. The proposed approach first divides the 360° image into multiple patches that replicate the positions (viewports) looked at by a subject while viewing a 360° image using a head mounted display. Next, a set of low-level features able to depict various properties of an image scene is extracted from each patch. The extracted features are combined to estimate the 360° saliency map. Finally, bias induced during image exploration and illumination variation is fine-tuned for estimating the final saliency map. The proposed method is evaluated using a benchmark 360° image dataset and is compared with two baselines and eight state-of-the-art approaches for saliency estimation. The obtained results show that the proposed model outperforms existing saliency estimation models. [ABSTRACT FROM AUTHOR]

An office chair for analyzing the seated posture variation during the performance of a stress-level test is presented in this work. To meet this aim, we placed a set of textile pressure sensors both on the backrest and on the seat of the chair. The position of the sensors was selected for maximizing the detection of variations of user's posture. The effectiveness of the designed system was evaluated through an experiment where increasing stress levels were obtained by administering a Stroop test. The collected results had been analyzed by considering three different time intervals based on the difficulty level of the test (low, medium, and high). A transition analysis conducted on postures assumed during the test showed that participants reached a different posture at the end of the test, when the cognitive engagement increased, with respect to the beginning. This evidence highlighted the presence of movement presumably due to the increased cognitive engagement. Overall, the performed analysis showed the proposed monitoring system could be used to identify body posture variations related to different levels of engagement of a seated user while performing cognitive tasks. [ABSTRACT FROM AUTHOR]

Augmented reality is one of the enabling technologies of the upcoming future. Its usage in working and learning scenarios may lead to a better quality of work and training by helping the operators during the most crucial stages of processes. Therefore, the automatic detection of stress during augmented reality experiences can be a valuable support to prevent consequences on people's health and foster the spreading of this technology. In this work, we present the design of a non-invasive stress assessment approach. The proposed system is based on the analysis of the head movements of people wearing a Head Mounted Display while performing stress-inducing tasks. First, we designed a subjective experiment consisting of two stress-related tests for data acquisition. Then, a statistical analysis of head movements has been performed to determine which features are representative of the presence of stress. Finally, a stress classifier based on a combination of Support Vector Machines has been designed and trained. The proposed approach achieved promising performances thus paving the way for further studies in this research direction.

Over the last few years applications based on the use of immersive environments, where physical and digital objects coexist and interact, have gained widespread attention. Thanks to the development of new visualization devices, even at low cost, and increasingly effective rendering and processing techniques, these applications are reaching a growing number of users. While the adoption of digital information makes it possible to provide immersive experiences in a number of different applications, there are still many unexplored aspects. In this work, a preliminary step to understand the impact of the scene content on human perception of the virtual 3D elements in a mixed reality has been performed. To this aim, a subjective test was designed and implemented to collect the reaction time of a set of users in a mixed reality application. In this test each user was asked to wear an augmented reality headset and to catch a virtual objects randomly appearing in the subject's field of view. We first estimated the detection accuracy through omitted, anticipated, and completed responses; then we related stimulus location, scene content and estimated accuracy. For this purpose, the area of stimulus presentation was divided into upper, lower, right, left, inner, and outer, to understand in which area responses were omitted and anticipated with respect to the central point of view. Experimental results show that, in addition to the saliency of the real scene, natural body gesture technology and limited field of view influenced human reaction time., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Arif, Brizzi, Carli and Battisti.)

In this paper, a multi-resolution method for depth estimation from dense image arrays is presented. Recent progress in consumer electronics has enabled the development of low cost hand-held plenoptic cameras. In these systems, multiple views of a scene are captured in a single shot by means of a micro-lens array placed on the focal point of the first camera lens, in front of the imaging sensor. These views can be processed jointly to obtain accurate depth maps. In this contribution, to reduce the computational complexity associated to global optimization schemes based on match cost functions, we make a local estimate based on the maximization of the total log-likelihood spatial density aggregated along the epipolar lines corresponding to each view pair. This method includes the local maximum likelihood estimation of the depth field based on epipolar plane images. To face the potential accuracy losses associated to the ambiguity problem that arises in flat surface regions while preserving bandwidth in correspondence of the edges, we adopt a multi-resolution scheme. In practice, the depth map resolution is reduced in regions where maximizing the higher resolution functional is ill-conditioned. The main benefits of the proposed system are in a reduced computational complexity and a high accuracy of the estimated depth. Experimental results show that the proposed scheme represents a good tradeoff among accuracy, robustness, and discontinuities handling.