Perceptually Optimized 3-D Transmission Over Wireless Networks

Cheng, Irene; Basu, Anup

doi:10.1109/tmm.2006.886291

Cited by 23 publications

(11 citation statements)

References 81 publications

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“…Wireless Networks [6] Nowadays the size of high-quality 3-D models is quite big. The 3-D models maybe damaged hardly by wireless transmission.…”

Section: Perceptually Optimized 3-d Transmission Overmentioning

confidence: 99%

Representation, Analysis of Bayesian Refinement Approximation Network: A Survey

Zhu¹,

Yang²

2021

Preprint

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After an artificial model background subtraction, the pixels have been labelled as foreground and background. Previous approaches to secondary processing the output for denoising usually use traditional methods such as the Bayesian refinement method. In this paper, we focus on using a modified U-Net model to approximate the result of the Bayesian refinement method and improve the result. In our modified U-Net model, the result of background subtraction from other models will be combined with the source image as input for learning the statistical distribution. Thus, the losing information caused by the background subtraction model can be restored from the source image. Moreover, since the part of the input image is already the output of the other background subtraction model, the feature extraction should be convenient, it only needs to change the labels of the noise pixels. Compare with traditional methods, using deep learning methods superiority in keeping details.

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“…Wireless Networks [6] Nowadays the size of high-quality 3-D models is quite big. The 3-D models maybe damaged hardly by wireless transmission.…”

Section: Perceptually Optimized 3-d Transmission Overmentioning

confidence: 99%

Representation, Analysis of Bayesian Refinement Approximation Network: A Survey

Zhu¹,

Yang²

2021

Preprint

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“…A JND-based metric was used in indirect illumination calculation [136], accounting for the spatial CSF and luminance adaption. Perceptual quality criteria have been devised [19,149,193] according to mesh and texture resolutions, for transmission of 3D geometric mesh vertices and texture data. Other relevant work can be found in [5,75,135].…”

Section: Pvqms For Computer-generated Visual Signalmentioning

confidence: 99%

Perceptual visual quality metrics: A survey

Wang

Kuo

2011

Journal of Visual Communication and Image Representation

839

346

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“…The paper by Cheng et al 11 on perceptually optimized 3D transmission over wireless networks, which states that perception varies with geometry changes following an exponential curve, and although our simplification levels were not distributed as theirs (i.e., logarithmically spaced), we ended up by also concentrating a larger amount of levels below 50%. Figure 3 shows all six versions of the ChinaDog model generated using QSlim.…”

Section: Simplification Levels and Algorithmsmentioning

confidence: 99%

Perceived quality assessment of polygonal meshes using observer studies: a new extended protocol

et al. 2008

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The complexity of a polygonal mesh is usually reduced by applying a simplification method, resulting in a similar mesh having less vertices and faces. Although several such methods have been developed, only a few observer studies are reported comparing the perceived quality of the simplified meshes, and it is not yet clear how the choice of a given method, and the level of simplification achieved, influence the quality of the resulting mesh, as perceived by the final users. Similar issues occur regarding other mesh processing methods such as smoothing. Mesh quality indices are the obvious less costly alternative to user studies, but it is also not clear how they relate to perceived quality, and which indices best describe the users behavior. This paper describes on going work concerning the evaluation of perceived quality of polygonal meshes using observer studies, while looking for a quality index which estimates user performance. In particular, given some results obtained in previous studies, a new experimental protocol was designed and a study involving 55 users was carried out, which allowed their validation, as well as further insight regarding mesh quality, as perceived by human observers.

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Perceptually Optimized 3-D Transmission Over Wireless Networks

Cited by 23 publications

References 81 publications

Representation, Analysis of Bayesian Refinement Approximation Network: A Survey

Representation, Analysis of Bayesian Refinement Approximation Network: A Survey

Perceptual visual quality metrics: A survey

Perceived quality assessment of polygonal meshes using observer studies: a new extended protocol

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