Perceptually optimized 3D transmission over wireless networks
SIGGRAPH '05 ACM SIGGRAPH 2005 Web program
Packet-loss modeling for perceptually optimized 3D transmission
Advances in Multimedia
A local roughness measure for 3D meshes and its application to visual masking
ACM Transactions on Applied Perception (TAP)
Robust and scalable transmission of arbitrary 3D models over wireless networks
Journal on Image and Video Processing - 3D Image and Video Processing
An Effective QoS Control Scheme for 3D Virtual Environments Based on User's Perception
IEICE - Transactions on Information and Systems
Optimal pixel aspect ratio for enhanced 3D TV visualization
Computer Vision and Image Understanding
Objective and subjective evaluation of static 3D mesh compression
Image Communication
Self-adaptive on-chip system based on cross-layer adaptation approach
International Journal of Reconfigurable Computing
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Many factors, such as the number of vertices and the resolution of texture, can affect the display quality of three-dimensional (3-D) objects. When the resources of a graphics system are not sufficient to render the ideal image, degradation is inevitable. It is, therefore, important to study how individual factors will affect the overall quality, and how the degradation can be controlled given limited resources. In this paper, the essential factors determining the display quality are reviewed. We then integrate two important ones, resolution of texture and resolution of wireframe, and use them in our model as a perceptual metric. We assess this metric using statistical data collected from a 3-D quality evaluation experiment. The statistical model and the methodology to assess the display quality metric are discussed. A preliminary study of the reliability of the estimates is also described. The contribution of this paper lies in: 1) determining the relative importance of wireframe versus texture resolution in perceptual quality evaluation and 2) proposing an experimental strategy for verifying and fitting a quantitative model that estimates 3-D perceptual quality. The proposed quantitative method is found to fit closely to subjective ratings by human observers based on preliminary experimental results.