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The purpose of this paper is to establish an easy-to-use questionnaire for subjective evaluations of visually induced motion sickness (VIMS) and visual fatigue caused by stereoscopic 3D (s3D) images. We reviewed previously used questionnaires and extracted 51 important subjective evaluation items from them. We then recruited 251 participants to observe 3D images designed to easily induce sickness or visual fatigue, and we asked them to respond to the 51 items. As a result of exploratory factor analysis, four factors were extracted according to their factor loadings, and the number of items was reduced to 21. Further processing by confirmatory factor analysis led to the selection of 15 items. Comparing mean ratings for each factor before and after item reduction indicated that item reduction did not significantly affect the participant responses. Therefore, the 15-item Visually Induced Symptoms Questionnaire (VISQ), can be used to evaluate VIMS and s3D visual fatigue. [ABSTRACT FROM AUTHOR]

The article discusses the role of 5G in mining organizations that can handle the requirements such as bandwidth, quality of service, latency, and positioning. 5G helps in complex drilling maneuvering, automated trucks and planning, and dispatch to handle several 3D video streams and manage highly complex tasks remotely. Satellites open up 5G to remote operations once latency becomes competitive remote operations, thus avoiding enormous upfront costs.

New digital approaches allow stereovision to be assessed with greater precision than current clinical stereo tests. Those current tests present a relatively narrow range of stimulus disparities in coarsely quantized steps. With dichoptic treatments for amblyopia emerging, more accurate assessment of especially coarse stereopsis becomes increasingly important for verifying their aim to improve 3D vision. We used digital testing in subjects of a large age range (4–59 years), with groups having both normal (n = 34) and impaired binocular vision due to unilateral amblyopia, with or without strabismus (n = 27). Random-dot stimuli were presented on a 3D monitor with shutter glasses. The test applies adaptive procedures to measure psychometric functions and provides thresholds with associated confidence intervals. Digital thresholds for controls (range 11–160 arcsec) and stereodeficient subjects (range 43–911 arcsec) were compared to the TNO, a standard clinical test which uses similar random-dot targets presented with anaglyph glasses. Agreement between digital and TNO thresholds varied with the level of stereopsis. Stereoacuity was measurable in several subjects who failed on the TNO. With the digital test we found good repeatability for both groups, with the indication of a small learning effect for subjects with coarse stereopsis. Thus, assessment of all target groups for new tests is important, and repeated testing before therapy may avoid confusing learning and treatment effects. Our digital approach supplies a large range of accurate stereo data in children and adults; together with its associated measure of variability, it will be useful in longitudinal treatment studies. [ABSTRACT FROM AUTHOR]

The interest of users towards three-dimensional (3D) video is gaining momentum due to the recent breakthroughs in 3D video entertainment, education, network, etc. technologies. In order to speed up the advancement of these technologies, monitoring quality of experience of the 3D video, which focuses on end user's point of view rather than service-oriented provisions, becomes a central concept among the researchers. Thanks to the stereoscopic viewing ability of human visual system (HVS), the depth perception evaluation of the 3D video can be considered as one of the most critical parts of this central concept. Due to the lack of efficiently and widely utilized objective metrics in literature, the depth perception assessment can currently only be ensured by cost and time-wise troublesome subjective measurements. Therefore, a no-reference objective metric, which is highly effective especially for on the fly depth perception assessment, is developed in this paper. Three proposed algorithms (i.e., Z direction motion, structural average depth and depth deviation) significant for the HVS to perceive the depth of the 3D video are integrated together while developing the proposed metric. Considering the outcomes of the proposed metric, it can be clearly stated that the provision of better 3D video experience to the end users can be accelerated in a timely fashion for the Future Internet multimedia services. [ABSTRACT FROM AUTHOR]

The perception of the visual landscape impact is a significant factor explaining the public's acceptance of energy infrastructure developments. Yet, there is lack of knowledge how people perceive and accept power lines in certain landscape types and in combination with wind turbines, a required setting to achieve goals of the energy turnaround. The goal of this work was to demonstrate how 3D point cloud visualizations could be used for an eye tracking study to systematically investigate the perception of landscape scenarios with power lines. 3D visualizations of near-natural and urban landscapes were prepared based on data from airborne and terrestrial laser scanning. These scenes were altered with varying amounts of the respective infrastructure, and they provided the stimuli in a laboratory experiment with 49 participants. Eye tracking and questionnaires served for measuring the participants' responses. The results show that the point cloud-based simulations offered suitable stimuli for the eye tracking study. Particularly for the analysis of guided perceptions, the approach fostered an understanding of disturbing landscape elements. A comparative in situ eye tracking study is recommended to further evaluate the quality of the point cloud simulations, whether they produce similar responses as in the real world. [ABSTRACT FROM AUTHOR]

We propose to generate novel animations from a set of elementary examples of video-based surface motion capture, under user-specified constraints. 4D surface capture animation is motivated by the increasing demand from media production for highly realistic 3D content. To this aim, data driven strategies that consider video-based information can produce animation with real shapes, kinematics and appearances. Our animations rely on the combination and the interpolation of textured 3D mesh data, which requires examining two aspects: (1) Shape geometry and (2) appearance. First, we propose an animation synthesis structure for the shape geometry, the Essential graph, that outperforms standard Motion graphs in optimality with respect to quantitative criteria, and we extend optimized interpolated transition algorithms to mesh data. Second, we propose a compact view-independent representation for the shape appearance. This representation encodes subject appearance changes due to viewpoint and illumination, and due to inaccuracies in geometric modelling independently. Besides providing compact representations, such decompositions allow for additional applications such as interpolation for animation. [ABSTRACT FROM AUTHOR]

Three-Dimensional Multi-View Video (3D-MVV) transmission over wireless networks suffers from losses. Therefore, the robust performance of 3D-MVV transmission techniques over wireless channels has become a recent hot research issue due to the restricted resources and the presence of severe channel errors. The 3D-MVV is composed of multiple video stream shots by several cameras around a single object, simultaneously. So, it is an urgent task to achieve high compression ratios to meet future bandwidth constraints. Unfortunately, the highly-compressed 3D-MVV data becomes more sensitive and vulnerable to packet losses, especially in the case of heavy channel errors. Thus, in this paper, we propose the application of a chaotic Baker map interleaving technique with equalization for efficient transmission of composite 3D-MVV compressed frames over an Orthogonal Frequency Division Multiplexing (OFDM) wireless channel. Rayleigh fading and Additive White Gaussian Noise (AWGN) are considered in the real scenario of 3D-MVV transmission. Firstly, the 3D-MVV content is compressed exploiting the intra- and inter-prediction correlations between frames. After that, a composite frame of luminance is generated from each four consecutive frames using Discrete Cosine Transform (DCT), which represents a second level of compression. The resultant composite frame is converted to binary data format. Then, chaotic interleaving is applied on the binary information prior to the modulation process. This chaotic interleaving is used to mitigate the OFDM induced Peak-to-Average Power Ratio (PAPR) problem and to reduce the wireless channel effects on the transmitted bit streams. It also adds a degree of encryption to the transmitted 3D-MVV compressed frames. To evaluate the performance of the proposed hybrid technique, several simulation experiments on different 3D-MVV frames have been executed. The experimental results show that the received 3D-MVV frames have high average Peak Signal-to-Noise Ratio (PSNR) gains up to 4.25 dB and a reduction of the average PAPR values by about 12 dB with the proposed hybrid technique compared to the other traditional techniques. [ABSTRACT FROM AUTHOR]

Highlights • The perceptual heterogeneous features are extracted for 3D videos quality assessment. • The binocular spatio-temporal internal generative mechanism to achieve multi-videos. • The multi-channel natural video statistics to characterize 3D video quality. • The AdaBoosting Radial Basis Function neural network to infer the overall quality. • The enhanced blind metric is robust and higher accuracy. Abstract 3D videos quality assessment (3D-VQA) is essential to various 3D video processing applications. However, it has not been well investigated on how to make use of perceptual multi-channel video information to improve 3D-VQA under different distortion categories and degrees, especially under asymmetrical distortions. In the paper, we propose a new blind 3D-VQA metric by jointly learning perceptually heterogeneous features. Firstly, a binocular spatio-temporal internal generative mechanism (BST-IGM) is proposed to decompose the views of 3D video into multi-channel videos. Then, we extract perceptually heterogeneous features by proposed multi-channel natural video statistics (MNVS) model, which are characterized 3D video information. Furthermore, a robust AdaBoosting Radial Basis Function (RBF) neural network is utilized to map the features to the overall quality of 3D video. On two benchmark databases, the extensive evaluations demonstrate that the proposed algorithm significantly outperforms several state-of-the-art quality metrics in term of prediction accuracy and robustness. [ABSTRACT FROM AUTHOR]

In this paper, we propose a Weighted Local sparse representation based Depth Image Super-Resolution (WLDISR) schemes aiming at improving the Virtual View Image (VVI) quality of 3D video system. Different from color images, depth images are mainly used to provide geometrical information in synthesizing VVI. Due to the view synthesis characteristics difference between textural structures and smooth regions of depth images, we divide the depth images into edge and smooth patches and learn two local dictionaries, respectively. Meanwhile, the weight term is derived and incorporated explicitly in the cost function to denote different importance of edge structures and smooth regions to the VVI quality. Then, local sparse representation and weighted sparse representation are jointly used in both dictionary learning and reconstruction phases in depth image super-resolution. Based on different optimizations on learning and reconstruction modules, three WLDISR schemes, WLDISR-D, WLDISR-R, and WLDISR-ALL, are proposed. Experimental results on 3D sequences demonstrate that the proposed WLDISR-D, WLDISR-R, and WLDISR-ALL schemes can achieve more than 1.9-, 2.03-, and 2.16-dB gains on average, respectively, in terms of the VVIs’ quality, as compared with the state-of-the-art schemes. In addition, the visual quality of VVIs is also improved. [ABSTRACT FROM AUTHOR]

Due to the popularity of 3D videos, 2D-to-3D video conversion has become a hot research topic for the past few years. The most critical issue in 3D video synthesis is the estimation of depth maps for the video frames. Numerous efforts have been devoted in fully automatic and semi-automatic depth estimation approaches, although the discontinuity of depth field and the ambiguity of motion boundary are still the main challenges in depth estimation. This paper proposes a semi-automatic structure-aware sparse-to-dense depth estimation method, which leverages the tensor voting at two different levels to propagate depth across frames. In the first level, a 4D tensor voting is performed to remove outliers caused by inaccurate motion estimation. Noticing that the 4D tensors of correctly matched points should lie on the smooth layer in the manifold, we utilize the variety saliency defined by the eigen-system of the tensor for outlier removal. In the second level, a high-dimensional tensor voting algorithm, incorporating spatial location, motion, and color into the tensor representation, is devised to propagate the depth from the sparse points to the entire image domain. By projecting the input feature into the tangent space, the relation between the location, motion, color, and the depth can be established by voting process. Extensive experiments on public data set validate the effectiveness of the proposed method in comparison with state-of-the-art depth estimation approaches. [ABSTRACT FROM AUTHOR]

Prostatic rhabdomyosarcoma (RMS) is a subtype of prostate sarcoma which is rarely reported in adults and usually huge in size. Although there is no consensus on the standard therapy to prostatic RMS, complete resection with negative margin is identified as the best way for maximum survival time. However, to remove a much enlarged prostate completely from a RMS patient is still a very difficult task for a skilled urologist so far. As three-dimension (3D) technology becomes more widely used in medicine, surgeons have the opportunity to challenge previously impossible surgery. In this paper, we reported a 36-year-old male patient with a 9.6*5.3*7.6 cm prostatic RMS. With the aid of 3D reconstructed video and printing model, the giant tumor was entirely removed without surgery complications and adjacent organs injury. The patient was alive and had no recurrence after 18 months from surgery. This case revealed that 3D reconstruction technology could help in the preoperative assessment and gave benefits to both patients and surgeons. [ABSTRACT FROM AUTHOR]

In wireless communication networks, additive channel noise and time varying multipath fading are considered amongst the main challenges and these effects will bring significant quality degradation to the transmitted 2D/3D video streams. This paper presents an efficient decoding algorithm for Distributed Video Coding (DVC) for enhanced performance of colour and depth based 3D video over error prone wireless channels. The maximum a-posteriori (MAP) algorithm for turbo decoding is modified considering the effects of the channel errors on both Wyner-Ziv and key frame bit streams of colour and depth videos. The proposed codec is simulated using a W-CDMA wireless channel model and the results are analyzed to determine the effect of the modifications. The performance of the state-of-the-art H.264/AVC video codec is also presented for comparison under similar conditions. The results show that the proposed modifications provide a significant improvement in the DVC codec performance under unfavourable channel conditions for colour plus depth based 3D video. [ABSTRACT FROM AUTHOR]

This paper presents two robust hybrid watermarking techniques for securing the Three-Dimensional High Efficiency Video Coding (3D-HEVC). The first watermarking technique is the homomorphic-transform-based Singular Value Decomposition (SVD) in Discrete Wavelet Transform (DWT) domain. The second watermarking technique is the three-level Discrete Stationary Wavelet Transform (DSWT) in Discrete Cosine Transform (DCT) domain. The objective of the two proposed hybrid watermarking techniques is to increase the immunity of the watermarked 3D-HEVC streams to attacks. Also, we propose a wavelet-based fusion technique to combine two depth watermark frames into one fused depth watermark frame. Then, the resultant fused depth watermark is encrypted using chaotic Baker map to increase the level of security. After that, the resultant chaotic encrypted fused depth watermark is embedded in the 3D-HEVC color frames using the proposed hybrid watermarking techniques to produce the watermarked 3D-HEVC streams. In addition to achieving multi-level security in the transmitted 3D-HEVC streams, the proposed hybrid techniques reduce the required bit rate for transmitting the color-plus-depth 3D-HEVC data over limited-bandwidth networks. The performance of the proposed hybrid techniques is compared with those of the state-of-the-art techniques. Extensive simulation results on standard 3D video sequences have been conducted in the presence of attacks. The obtained results confirm that the proposed hybrid fusion-encryption-watermarking techniques achieve not only a good perceptual quality with high Peak Signal-to-Noise Ratio (PSNR) values and less bit rate, but also high correlation coefficient values between the original and extracted watermarks in the presence of attacks. Furthermore, the proposed hybrid techniques improve the capacity of information embedding and the robustness without affecting the perceptual quality of the original 3D-HEVC frames. Indeed, the extraction of the encrypted, fused, primary, and secondary depth watermark frames is possible in the presence of attacks. [ABSTRACT FROM AUTHOR]

A new type of optical in-line holographic three-dimensional (3-D) video display system with omnidirectional viewing zones by using a center-symmetric multi-sideband filtering method is proposed. The frequency spectrum of the complex hologram is center-symmetrically divided into even numbers of multi-sidebands and partitioned into two groups by being alternately selected along the angular direction. One group corresponding to the conjugate image is filtered out in both of the digital-recording and optical-reconstruction processes with their specific filter masks. Then, from the other group, the real image, which can be viewed from almost all directions with a set of angularly-subdivided viewing zones, is reconstructed on the optical 4- f lens system without a conjugate image. Fourier-optical analysis and experiments with 3-D objects in motion confirm the feasibility of the proposed system. [ABSTRACT FROM AUTHOR]

The three-dimensional video (3DV) is composed of variable-length stream sequences captured via diversified cameras surrounding an object. Thus, it is an urgent task to accomplish sufficient encoding to be compatible with incoming bandwidth demands, while achieving a recommended 3DV reception performance. In the 3DV compression framework, the lost macro-blocks (MBs) might propagate into the following frames and the adjoining views. Therefore, it is obligatory to avoid error propagation by concealing the corrupted MBs at the decoder through the utilization of appropriate post-processing error concealment (EC) techniques. The existing EC algorithms fundamentally exploit the temporal, inter-view, and spatial matching within the 3DV frames and views to reconstruct the disparity vectors (DVs) and motion vectors (MVs) of the corrupted MBs. Unluckily, in the state of high severe corruptions and heavily erroneous MBs, these concealment algorithms are predominantly unreliable and might give unreliable 3DV quality. Thence, in this work, we suggest the utilization of the outer block boundary matching algorithm to estimate the MVs and the directional interpolation EC algorithm to estimate the DVs of the erroneous MBs. After that, the Bayesian Kalman filter (BKF) is employed because of its efficiency to filter out the inherent errors in the previously predicted DVs and MVs to accomplish better 3D video performance. Experimental results on standard 3DV sequences demonstrate that the suggested BKF-based EC scheme is more powerful with heavy losses. It subjectively and objectively outperforms the traditional concealment techniques at severely random and bursty packet loss rates (PLRs). [ABSTRACT FROM AUTHOR]

This paper proposes an interaction design architecture and an interaction protocol for the construction of pedagogical agents acting in distributed 3D learning environments. Agents designed based on the proposed architecture are able to interact verbally, non-verbally or both with the students, combining empathic and pedagogical behavioral parameters in order to support students during online educational activities. The representation of the agent results from both pedagogical and emotional factors and is related with the learning environment and its technology. The agent logic is based on three types of the learning environment’s events: (a) emotional events, (b) pedagogical events and (c) events that are triggered by the environment itself. The proposed architecture is validated through the implementation of an autonomous pedagogical-empathic agent in the virtual environment of OpenSim. The agent observes students’ anxiety during the learning process and reacts when their anxiety level is considered high. [ABSTRACT FROM AUTHOR]

Target detection based on image/video, being involved to deal with the geometry and scale deformation, as well as the change in the form of movement caused by camera imaging, algorithms are always designed complexly. Though, object shelter and adhesion still cannot be well resolved. Considering of that, a new method for target detection on true 3D space based on the inverse projection transformation and a mixing component model is proposed. Firstly, the inverse projective arrays parallel to target local surface are established on 3D space. Then, the 2D image is inversely projected to these planes through 3D point cloud re-projection, and a lot of inverse projective images with target local apparent characteristics are gained. After that, component HOG feature dictionaries are trained using the inverse projective images as samples, and on account of it, sparse decomposition approach is adopted to detect target local components. Finally, 3D centroid clustering for all the components is further used to identify the target. Experiment results indicate that the target detection method on true 3D space based on multi-components model and inverse projection transformation can not only deal with the object occlusion and adhesion perfectly, but also adapt to the multi-angle target detection well, and the accuracy and speed is far beyond that of the algorithm on 2D image. [ABSTRACT FROM AUTHOR]

The authors introduce a novel marker-less multi-camera setup that allows easy synchronisation between 3D cameras as well as a novel pose estimation method that is calculated on the fly based on the human body being tracked, and thus requires no calibration session nor special calibration equipment. They show high accuracy in both calibration and data merging and is on par with equipment-based calibration. They deduce several insights and practical guidelines for the camera setup and for the preferred data merging methods. Finally, they present a test case that computerises the Fugl-Meyer stroke rehabilitation protocol using the authors' multi-sensor capture system. They conducted a Helsinki-approved research in a hospital in which they collected data on stroke patients and healthy subjects using their multi-camera system. Spatio-temporal features were extracted from the acquired data and machine learning-based evaluations were applied. Results showed that patients and healthy subjects can be correctly classified at a rate of above 90%. Furthermore, they show that the most significant features in the classification are strongly correlated with the Fugl-Meyer guidelines. This demonstrates the feasibility of a low-cost, flexible and non-invasive motion capture system that can potentially be operated in a home setting. [ABSTRACT FROM AUTHOR]

Abstract Facial expression involves a dynamic process, leading to the variation of different facial components over time. Thus, dynamic descriptors are essential for recognising facial expressions. In this paper, we extend the spatial pyramid histogram of gradients to spatio-temporal domain to give 3-dimensional facial features. To enhance the spatial information, we divide the whole face region into a group of smaller local regions to extract local 3D features, and a weighting strategy based on fisher separation criterion is proposed to enhance the discrimination ability of local features. A multi-class classifier based on support vector machine is applied for recognising facial expressions. Experiments on the CK+ and MMI datasets using leave-one-out cross validation scheme show that the proposed framework perform better than using the descriptor of simple concatenation. Compared with state-of-the-art methods, the proposed framework demonstrates a superior performance. [ABSTRACT FROM AUTHOR]

This work introduces a new scheme for action unit detection in 3D facial videos. Sets of features that define action unit activation in a robust manner are proposed. These features are computed based on eight detected facial landmarks on each facial mesh that involve angles, areas and distances. Support vector machine classifiers are then trained using the above features in order to perform action unit detection. The proposed AU detection scheme is used in a dynamic 3D facial expression retrieval and recognition pipeline, highlighting the most important AU s, in terms of providing facial expression information, and at the same time, resulting in better performance than state-of-the-art methodologies. [ABSTRACT FROM AUTHOR]

Keywords: coronary CT angiography; coronary-pulmonary artery fistula; three-dimensional visualization technology 2 Lee CM, Song SY, Jeon SC, Park CK, Choi YW, Lee Y. Characteristics of coronary artery to pulmonary artery fistula on coronary computed tomography angiography. Coronary CT angiography, coronary-pulmonary artery fistula, three-dimensional visualization technology. [Extracted from the article]

Video streaming is a foremost and growing contributor in the ever increasing Internet traffic. Since last two decades, due to the enhancement in cameras and image processing technology, we have seen a shift towards multi-view plus depth (MVD) technology from traditional 2D and 3D video technology. This growth comes with deep changes in the Internet bandwidth, video coding and network technologies, which smoothed the mode for delivery of MVD content to end-users over the Internet. Since, MVD contains large amounts of data than single view video, it requires more bandwidth. It is a challenging task for network service provider to deliver such views with the best user’s Quality of Experience(QoE) in dynamic network condition. Also, Internet is known to be prone to packet loss, bandwidth variation, delay and network congestion, which may prevent video packets from being delivered on time. Besides that, different capabilities of end user’s devices in terms of computing power, display, and access link capacity are other challenges. As consequences, the viewing experiences of 3D videos may well degrade, if the quality-aware adaptation techniques are not deployed. In this article, our work concentrates to present a comprehensive analysis of a dynamic network environment for streaming of 3D MVD over Internet (HTTP). We analyzed the effect of different adaptation of decision strategies and formulated a new quality-aware adaptation technique. The proposed technique is promoting from layer based video coding in terms of transmitted views scalability. The results of MVD streaming experiment, using the proposed approach have shown that the video quality of perceptual 3D improves significantly, as an effect of proposed quality aware adaptation even in adverse network conditions. [ABSTRACT FROM AUTHOR]

The article focuses on the impact of Virtual reality (VR) and Augmented Reality (AR) on various general life aspects such as natural environment, cultural past, and new technologies to be emerged in the future. Topics discussed include application of virtualizing tools to archaeological reconstruction such as three dimension tour of Sistine Chapel, Vatican City, Domus Aurea in Rome, and Antique Museum of Basel.

In this letter, we propose an unsupervised salient object detection method in three-dimensional videos. Both temporal and depth information are efficiently considered, and multiscale architecture and graph-based refinement are built to improve accuracy and robustness. First, the input video frame is segmented into nonoverlapping superpixels by combining both appearance and depth information at the input. A multiscale architecture is also deployed after the segmentation with different segmentation parameters. Second, the initial saliency score of each segmented superpixel in each scale is calculated via global contrast, which is defined by appearance, depth, and motion cues from two consecutive frames. Third, the initial saliency in each scale is refined by smoothing over graphs built by three spatial–temporal feature priors—color, depth, and motion. Finally, the result is obtained by fusing three refined saliency maps in three scales. The experiments on two widely used datasets illustrate that our method outperforms state-of-the-art algorithms in terms of accuracy, robustness, and reliability. [ABSTRACT FROM AUTHOR]

The quality of a 3D video display depends on virtual view synthesis process which is affected by the bit allocation criterion. The performance of a bit allocation algorithm is dependent on various encoding parameters like quantization parameter, motion vector, mode selection, and so on. Rate-distortion optimization (RDO) is used to efficiently allocate bits with minimum distortion. In 3D video, rate-distortion (RD) property of synthesized view is used to assign bits between texture video and depth map. Existing literature on bit allocation methods use mean square error (MSE) as distortion metric which is not suitable for measuring perceptual quality. In this paper, we propose structural similarity (SSIM)-based joint bit allocation scheme to enhance visual quality of 3D video. Perceptual quality of a synthesized view depends on texture and depth map quality. Thus, SSIM-based RDO is performed on both texture and depth map where SSIM is used as distortion metric in mode decision and motion estimation. SSIM-based distortion model for synthesized view is determined experimentally. As SSIM cannot be related to quantization step, SSIM-MSE relation is used to convert distortion model in terms of MSE. The Lagrange multiplier method is used to solve the bit allocation problem. The proposed algorithm is implemented using 3DV-ATM as well as HEVC. RD curves show reduction in bitrate with an improvement in SSIM of synthesized view. [ABSTRACT FROM AUTHOR]

Background: Studies on Contemplative Landscapes (CL) show that not only do they have high ecological and visual values and are preferred by a majority of people, but they also can be beneficial to our mental health and well-being. Physical attributes of CL have been studied and operationalized, which has led to the development of the psychometric measurement tool called the Contemplative Landscape Questionnaire (CLQ) (1). Objectives: In the present study, we applied an experimental approach to the analysis of CL. We hypothesized that, when compared to Non-Contemplative Landscapes (NCL), they would induce higher frontal alpha power asymmetry, higher temporal beta power asymmetry and lower bilateral frontal beta power. Methods: Thirty-two healthy individuals (12 female) took part in the study. During the experimental protocol, participants were asked to passively view 12 landscapes, six CL and six NCL, while continuous EEG was recorded in a within-subjects design. Results: We found significantly increased power in the beta frequency band of the right temporal brain regions in the viewings of CL compared to NCL Conclusions: The findings suggest that Contemplative Landscapes capture more visual, stimuli-driven attention from the viewers and can be linked with switching attention systems (described in Attention Restoration Theory), which is compatible with a stress reduction mechanism. [ABSTRACT FROM AUTHOR]

Video game technology is changing from 2D to 3D and virtual reality (VR) graphics. In this research, we analyze how an identical video game that is either played in a 2D, stereoscopic 3D or Head-Mounted-Display (HMD) VR version is experienced by the players, and how brands that are placed in the video game are affected. The game related variables, which are analyzed, are presence, attitude towards the video game and arousal while playing the video game. Brand placement related variables are attitude towards the placed brands and memory (recall and recognition) for the placed brands. 237 players took part in the main study and played a jump’n’run game consisting of three levels. Results indicate that presence was higher in the HMD VR than in the stereoscopic 3D than in the 2D video game, but neither arousal nor attitude towards the video game differed. Memory for the placed brands was lower in the HMD VR than in the stereoscopic 3D than in the 2D video game, whereas attitudes towards the brands were not affected. A post hoc study (n = 53) shows that cognitive load was highest in the VR game, and lowest in the 3D game. Subjects reported higher levels of dizziness and motion-sickness in the VR game than in the 3D and in the 2D game. Limitations are addressed and implications for researchers, marketers and video game developers are outlined. [ABSTRACT FROM AUTHOR]

In 3D video coding systems, depth maps are not displayed to the viewers, but provide the geometric information to generate virtual views. To ensure the quality of virtual views, the rate-distortion optimization (RDO) in depth map coding adopts the virtual view distortion as the distortion item. The virtual view distortion comes from the reconstructed color video distortion and depth distortion. It is usually recognized that the virtual view distortion caused by reconstructed color video distortion is independent of that in depth map coding. Preliminary experiments reveal that the virtual view distortion in depth map coding is also influenced by the reconstructed color video distortion. Therefore, we proposed a novel distortion criterion of depth map coding in which the reconstructed color video distortion is modeled and joins into the virtual view distortion calculation. Correspondingly, the associated Lagrange multiplier is also proposed. Experimental results demonstrate that the method by integrating the proposed distortion criterion into RDO for depth map coding can achieve an average 12.72% bitrate saving compared with SSD based RDO method and can also lead a bitrate reduction (0.64%) compared with the existing distortion estimation method in the current 3D-HEVC reference software. With the associated Lagrange multiplier, the proposed distortion criterion can achieve 12.98% bitrate saving compared with SSD based RDO method on average. [ABSTRACT FROM AUTHOR]

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We studied highly realistic communication systems using a super multiview three-dimensional (3-D) video system. We propose the developed glasses-free 200-in. 3-D display using ∼200 high-definition (HD) projector units to reconstruct natural life-size 3-D moving objects, such as cars and humans. We also analyzed the optimal arrangement of the multiview camera system for the 3-D display. In the experiments, we developed a prototype super multiview 3-D camera system using compact HD video cameras with real-time convergence compensation circuits that correct the captured images via image processing optimized for the display. We also performed demonstration experiments using the developed 3-D display and camera system in a public area. As a result, we highlight several possibilities for actual applications of the glasses-free super multiview 3-D video system. [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]

When dealing with networks, performance management through conventional quality of service (QoS)-based methods becomes difficult and is often ineffective. In fact, quality emerges as an end-to-end factor, for it is particularly sensitive to the end-user perception of the overall service, i.e., the user’s quality of experience (QoE). However, the two are not independent from each other and their relationship has to be studied through metrics that go beyond the typical network parameters. To better explore the value of assessing QoE alongside QoS in high-speed, lossy networks, this paper presents an experimental methodology to understand the relation between network QoS onto service QoE, with the aim to perform a combined network-service assessment. Using video streaming services as the test-case (given their extended usage nowadays), in this paper, we provide studies on three network-impaired video-sets with the aim to provide a comprehensive evaluation of the effects of networks on video quality. First, the ReTRIeVED video set provides the means to understand the most impairing effects on networks. Furthermore, it triggered the idea to create our own sets, specialized in the most impairing conditions for 2-D and 3-D: the LIMP Video Quality Database and the 3-D-HEVC-Net Video Quality Database. Our study and methodology are meant to provide service providers with the means to pinpoint the working boundaries of their video-sets in face of different network conditions. At the same time, network operators may use our findings to predict how network control policies affect the user’s perception of the service. [ABSTRACT FROM AUTHOR]

The aim of this research is to investigate the suitability of truncated correlation photothermal coherence tomography (TC-PCT) for the non-destructive imaging of a replica of a real inlay to identify subsurface features that often are invisible areas of vulnerability and damage. Defects of inlays involve glue-rich areas, glue-starved areas, termite attack, insect damage, and laminar splitting. These defects have the potential to result in extensive damage to the art design layers of inlays. Therefore, there is a need for an imaging technique to visualize and determine the location of defects within the sample. The recently introduced TC-PCT modality proved capable of providing 3-D images of specimens with high axial resolution, deep subsurface depth profiling capability, and high signal-to-noise ratio (SNR). Therefore, in this study the authors used TC-PCT to image a fabricated inlay sample with various natural and artificial defects in the middle and top layers. The inlay in question reproduces to scale a piece of art preserved in the “Mirror room” of the Castle Laffitte in France. It was built by a professional restorer following the ancient procedure named element by element . Planar TC-PCT images of the inlay were stacked coherently to provide 3-D visualization of areas with known defects in the sample. The experimental results demonstrated the identification of defects such as empty holes, a hole filled with stucco, subsurface delaminations and natural features such as a wood knot and wood grain in different layers of the sample. For this wooden sample that has a very low thermal diffusivity, a depth range of 2 mm was achieved. [ABSTRACT FROM AUTHOR]