Get Advanced Video Coding: Principles and Techniques, Volume 7: PDF

By K.N. Ngan, T. Meier, D. Chai

ISBN-10: 044482667X

ISBN-13: 9780444826671

In recent times, the paradigm of video coding has shifted from that of a frame-based method of a content-based strategy, fairly with the finalization of the ISO multimedia coding normal, MPEG-4. MPEG-4 is the rising typical for the coding of multimedia content material. It defines a syntax for a collection of content-based functionalities, specifically, content-based interactivity, compression and common entry. notwithstanding, it doesn't specify how the video content material is to be generated. To generate the video content material, video needs to be segmented into video items and tracked as they transverse around the video frames. This booklet addresses the tricky challenge of video segmentation, and the extraction and monitoring of video item planes as outlined in MPEG-4. It then specializes in the categorical factor of face segmentation and coding as utilized to videoconferencing on the way to increase the standard of videoconferencing photos specially within the facial quarter.
Modal-based coding is a content-based coding strategy used to code man made gadgets that experience develop into an incredible a part of video content material. It ends up in tremendous low bit charges simply because purely the parameters had to signify the modal are transmitted. Model-based coding is integrated to supply heritage info for the substitute item coding in MPEG-4. finally, MPEG-4, the 1st coding commonplace for multimedia content material is defined intimately. the themes coated contain the coding of audio items, the coding of typical and artificial video gadgets, and blunder resilience.
Advanced Video Coding is likely one of the first books on content-based coding and MPEG-4 coding ordinary. It serves as a great info resource and reference for either researchers and training engineers.

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Additional info for Advanced Video Coding: Principles and Techniques, Volume 7: The Content-based Approach

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Each pixel (i, j) is assigned a label m C { 0 , . . , K - 1} so that X(i, j) = m means (i, j) belongs to region m. Notice that K, which is usually specified as an input parameter, is not the number of regions in the resulting partition. Normally, there will be far more regions than K, hence different regions are allowed to share the same label rn as long as these regions are not neighbors of each other. The aim is to find the MAP estimate of X. Thus, we want to find the most likely segmentation X, given the gray-scale image O.

Most motion estimation techniques neither identify these so-called occlusion regions nor treat them specially. Instead, they are simply accepted as regions of high compensation error. For segmentation, however, occlusion regions cannot be neglected because this would have a negative effect on the accuracy of the motion boundary location. All the difficulties affecting motion estimation mentioned above suggest that the resulting motion field has to be carefully interpreted. Apparent motion alone is not well-suited for segmentation because an accurate motion field is required.

By removing the high temporal redundancy present in video sequences~ high compression ratios can be achieved. Recovering the true motion of objects with high motion boundary ~ccuracy, which is crucial for segmentation~ plays only a minor role in coding as long as the prediction error is low. Schunck [77] commented on this issue by stating "... Image compression has not forced the development of image flow estimation algorithms that handle discontinuities because image compression does not require perfect estimation of the motion and does not require the detection of motion boundaries.

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Advanced Video Coding: Principles and Techniques, Volume 7: The Content-based Approach by K.N. Ngan, T. Meier, D. Chai


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