Perceptual preference of S3D over 2D for HDTV in dependence of video quality and depth

International audience3D video quality of experience (QoE) is a multidimensional problem and many factors contribute to the global experience by the user. Due to this multidimensionality, this paper evaluates the integral 3D video QoE and relates it with image quality and depth. Subjective tests have been conducted using paired comparison to evaluate 3D QoE and the preference of 3D over 2D with different combinations of coding conditions. Depth scores were available from previous work and were used to check their relation with 3DQoE; the difference between 2D and 3D QoE is found to be a function of the picture quality, and the desired preference of 3D presentation over 2D can be reached when pictorial quality is high enough (VQM score lower than 0.24). A factor ranging from 0.08 to 0.76 with a mean of 0.71 between pictorial quality and preference of 3D was also found

Gradient-based 2D-to-3D Conversion for Soccer Videos

A wide spread adoption of 3D videos and technologies is hindered by the lack of high-quality 3D content. One promising solution to address this problem is to use automated 2D-to-3D conversion. However, current conversion methods, while general, produce low-quality results with artifacts that are not acceptable to many viewers. We address this problem by showing how to construct a high-quality, domain-specific conversion method for soccer videos. We propose a novel, data-driven method that generates stereoscopic frames by transferring depth information from similar frames in a database of 3D stereoscopic videos. Creating a database of 3D stereoscopic videos with accurate depth is, however, very difficult. One of the key findings in this paper is showing that computer generated content in current sports computer games can be used to generate high-quality 3D video reference database for 2D-to-3D conversion methods. Once we retrieve similar 3D video frames, our technique transfers depth gradients to the target frame while respecting object boundaries. It then computes depth maps from the gradients, and generates the output stereoscopic video. We implement our method and validate it by conducting user-studies that evaluate depth perception and visual comfort of the converted 3D videos. We show that our method produces high-quality 3D videos that are almost indistinguishable from videos shot by stereo cameras. In addition, our method significantly outperforms the current state-of-the-art method. For example, up to 20% improvement in the perceived depth is achieved by our method, which translates to improving the mean opinion score from Good to Excellent.Qatar Computing Research Institute-CSAIL PartnershipNational Science Foundation (U.S.) (Grant IIS-1111415

Quality-controlled audio-visual depth in stereoscopic 3D media

BACKGROUND: The literature proposes several algorithms that produce “quality-controlled” stereoscopic depth in 3D films by limiting the stereoscopic depth to a defined depth budget. Like stereoscopic displays, spatial sound systems provide the listener with enhanced (auditory) depth cues, and are now commercially available in multiple forms. AIM: We investigate the implications of introducing auditory depth cues to quality-controlled 3D media, by asking: “Is it important to quality-control audio-visual depth by considering audio-visual interactions, when integrating stereoscopic display and spatial sound systems?” MOTIVATION: There are several reports in literature of such “audio-visual interactions”, in which visual and auditory perception influence each other. We seek to answer our research question by investigating whether these audio-visual interactions could extend the depth budget used in quality-controlled 3D media. METHOD/CONCLUSIONS: The related literature is reviewed before presenting four novel experiments that build upon each other’s conclusions. In the first experiment, we show that content created with a stereoscopic depth budget creates measurable positive changes in audiences’ attitude towards 3D films. These changes are repeatable for different locations, displays and content. In the second experiment we calibrate an audio-visual display system and use it to measure the minimum audible depth difference. Our data is used to formulate recommendations for content designers and systems engineers. These recommendations include the design of an auditory depth perception screening test. We then show that an auditory-visual stimulus with a nearer auditory depth is perceived as nearer. We measure the impact of this effect upon a relative depth judgement, and investigate how the impact varies with audio-visual depth separation. Finally, the size of the cross-modal bias in depth is measured, from which we conclude that sound does have the potential to extend the depth budget by a small, but perceivable, amount

Providing 3D video services: the challenge from 2D to 3DTV quality of experience

Recently, three-dimensional (3D) video has decisively burst onto the entertainment industry scene, and has arrived in households even before the standardization process has been completed. 3D television (3DTV) adoption and deployment can be seen as a major leap in television history, similar to previous transitions from black and white (B&W) to color, from analog to digital television (TV), and from standard definition to high definition. In this paper, we analyze current 3D video technology trends in order to define a taxonomy of the availability and possible introduction of 3D-based services. We also propose an audiovisual network services architecture which provides a smooth transition from two-dimensional (2D) to 3DTV in an Internet Protocol (IP)-based scenario. Based on subjective assessment tests, we also analyze those factors which will influence the quality of experience in those 3D video services, focusing on effects of both coding and transmission errors. In addition, examples of the application of the architecture and results of assessment tests are provided

Binocular Rivalry Oriented Predictive Auto-Encoding Network for Blind Stereoscopic Image Quality Measurement

Stereoscopic image quality measurement (SIQM) has become increasingly important for guiding stereo image processing and commutation systems due to the widespread usage of 3D contents. Compared with conventional methods which are relied on hand-crafted features, deep learning oriented measurements have achieved remarkable performance in recent years. However, most existing deep SIQM evaluators are not specifically built for stereoscopic contents and consider little prior domain knowledge of the 3D human visual system (HVS) in network design. In this paper, we develop a Predictive Auto-encoDing Network (PAD-Net) for blind/No-Reference stereoscopic image quality measurement. In the first stage, inspired by the predictive coding theory that the cognition system tries to match bottom-up visual signal with top-down predictions, we adopt the encoder-decoder architecture to reconstruct the distorted inputs. Besides, motivated by the binocular rivalry phenomenon, we leverage the likelihood and prior maps generated from the predictive coding process in the Siamese framework for assisting SIQM. In the second stage, quality regression network is applied to the fusion image for acquiring the perceptual quality prediction. The performance of PAD-Net has been extensively evaluated on three benchmark databases and the superiority has been well validated on both symmetrically and asymmetrically distorted stereoscopic images under various distortion types

3D video quality of experience - influence of scale and crosstalk

This paper gives an overview of three recent studies by the authors on the topic of 3D video Quality of Experience (QoE). Two of studies [1,2] investigated different psychological dimension that may be needed for describing 3D video QoE and the third the visibility and annoyance of crosstalk[3]. The results shows that the video quality scale could be sufficient for evaluating S3D video experience for coding and spatial resolution reduction distortions. It was also confirmed that with a more complex mixture of degradations more than one scale should be used to capture the QoE in these cases. The study found a linear relationship between the perceived crosstalk and the amount of crosstalk

Perceived Depth Control in Stereoscopic Cinematography

Despite the recent explosion of interest in the stereoscopic 3D (S3D) technology, the ultimate prevailing of the S3D medium is still significantly hindered by adverse effects regarding the S3D viewing discomfort. This thesis attempts to improve the S3D viewing experience by investigating perceived depth control methods in stereoscopic cinematography on desktop 3D displays. The main contributions of this work are: (1) A new method was developed to carry out human factors studies on identifying the practical limits of the 3D Comfort Zone on a given 3D display. Our results suggest that it is necessary for cinematographers to identify the specific limits of 3D Comfort Zone on the target 3D display as different 3D systems have different ranges for the 3D Comfort Zone. (2) A new dynamic depth mapping approach was proposed to improve the depth perception in stereoscopic cinematography. The results of a human-based experiment confirmed its advantages in controlling the perceived depth in viewing 3D motion pictures over the existing depth mapping methods. (3) The practicability of employing the Depth of Field (DoF) blur technique in S3D was also investigated. Our results indicate that applying the DoF blur simulation on stereoscopic content may not improve the S3D viewing experience without the real time information about what the viewer is looking at. Finally, a basic guideline for stereoscopic cinematography was introduced to summarise the new findings of this thesis alongside several well-known key factors in 3D cinematography. It is our assumption that this guideline will be of particular interest not only to 3D filmmaking but also to 3D gaming, sports broadcasting, and TV production

HiddenGazeStereo: Hiding Gaze-Contingent Disparity Remapping for 2D-Compatible Natural 3D Viewing

Stereoscopic 3D displays (S3D), the most popular consumer display devices for 3D presentation, have a few problems that degrade the natural visual experience, such as unnatural relationships between eye vergence and accommodation, and severe image blurring (ghost) for viewers without stereo glasses. To simultaneously solve these problems, we combine gaze-contingent disparity remapping with Hidden Stereo in a manner that mutually compensates for their respective shortcomings. Gaze-contingent disparity remapping can reduce the vergence-accommodation conflict by shifting the disparity distribution around the gaze position to be centered on the display plane. Hidden Stereo can synthesize 2D-compatible 3D stereo images that do not produce any ghosting artifacts when the images for the two eyes are linearly fused. Thus, by using our new gaze-contingent display, while one viewer with glasses enjoys natural 3D content, many other glassless viewers enjoy clear 2D content. To enable real-time synthesis, we accelerate Hidden Stereo conversion by limiting the processing to each horizontal scanline. Through a user study using a variety of 3D scenes, we demonstrate that Hidden Stereo can effectively hide disparity information to glassless viewers despite the dynamic disparity manipulations. Moreover, we show that our method can alleviate the limitation of Hidden Stereo --the narrow reproducible disparity range-- by manipulating the disparity so that the depth information around the gaze position is maximally preserved