KEYWORDS: Visualization, Image quality, 3D modeling, 3D image processing, Image compression, Visual process modeling, 3D displays, Video, Distortion, Molybdenum
Modern stereoscopic 3DTV brings new QoE (quality of experience) to viewers, which not only enhances the 3D
sensation due to the added binocular depth, but may also induce new problems such as visual discomfort. Subjective
quality assessment is the conventional method to assess the QoE. However, the conventional perceived image quality
concept is not enough to reveal the advantages and the drawbacks of stereoscopic images in 3DTV. Higher-level
concepts such as visual experience were proposed to represent the overall visual QoE for stereoscopic images. In this
paper, both the higher-level concept quality indicator, i.e. visual experience and the basic level concepts quality
indicators including image quality, depth quantity, and visual comfort are defined. We aim to explore 3D QoE by
constructing the visual experience as a weight sum of image quality, depth quantity and visual comfort. Two experiments
in which depth quantity and image quality are varied respectively are designed to validate this model. In the first
experiment, the stimuli consist of three natural scenes and for each scene, there are four levels of perceived depth
variation in terms of depth of focus: 0, 0.1, 0.2 and 0.3 diopters. In the second experiment, five levels of JPEG 2000
compression ratio, 0, 50, 100, 175 and 250 are used to represent the image quality variation. Subjective quality
assessments based on the SAMVIQ method are used in both experiments to evaluate the subject's opinion in basic level
quality indicators as well as the higher-level indicator. Statistical analysis of result reveals how the perceived depth and
image quality variation affect different perceptual scales as well as the relationship between different quality aspects.
Human binocular depth perception, the most important element brought by 3DTV, is proved to be closely connected to
not only the content acquisition (camera focal length, camera baseline and etc.) but also the viewing environment
(viewing distance, screen size and etc.). Conventional 3D stereography rule in the literature usually consider the general
viewing condition and basic human factors to guide the content acquisition, such as assuming human inter-pupil baseline
as the maximum disparity. A lot of new elements or problems of stereoscopic viewing was not considered or precisely
defined so that advanced shooting rule is needed to guarantee the overall quality of stereoscopic video. In this paper, we
proposed a new stereoscopic video shooting rule considering two most important issues in 3DTV: stereoscopic distortion
and comfortable viewing zone. Firstly, a mathematic model mapping the camera space to visualization space is
established in order to geometrically estimate the stereoscopic depth distortion. Depth and shape distortion factors are
defined and used to describe the stereoscopic distortion. Secondly, comfortable viewing zone (or Depth of focus) is
considered to reduce the problem of visual discomfort and visual fatigue. The new shooting rule is to optimize the
camera parameters (focal length, camera baseline and etc.) in order to control depth and shape distortion and also
guarantee that the perceived scene is located in comfortable viewing zone as possible. However, in some scenarios, the
above two conditions cannot be fulfill simultaneously, even sometimes contradict with each other so that priority should
be decided. In this paper, experimental stereoscopic synthetic content generation with various sets of camera parameters
and various sets of scenes representing different depth range are presented. Justification of the proposed new shooting
rule is based on 3D concepts (depth rendering, visual comfort and visual experience) subjective video assessment. The
results of this study will provide a new method to propose camera parameters based on management of new criteria
(shape distortion and depth of focus) in order to produce optimized stereoscopic images and videos.
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