By K.N. Ngan, T. Meier, D. Chai
In recent times, the paradigm of video coding has shifted from that of a frame-based method of a content-based process, quite with the finalization of the ISO multimedia coding usual, MPEG-4. MPEG-4 is the rising ordinary for the coding of multimedia content material. It defines a syntax for a suite of content-based functionalities, particularly, 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 should be segmented into video items and tracked as they transverse around the video frames. This ebook addresses the tough 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 for you to enhance the standard of videoconferencing pictures in particular within the facial sector. Modal-based coding is a content-based coding procedure used to code man made gadgets that experience develop into a big a part of video content material. It leads to tremendous low bit premiums simply because purely the parameters had to characterize the modal are transmitted. Model-based coding is integrated to supply history details for the artificial item coding in MPEG-4. finally, MPEG-4, the 1st coding general for multimedia content material is defined intimately. the themes lined contain the coding of audio items, the coding of traditional and artificial video gadgets, and blunder resilience. complicated Video Coding is among the first books on content-based coding and MPEG-4 coding commonplace. It serves as a great details resource and reference for either researchers and training engineers.
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Additional info for Advanced Video Coding: Principles and Techniques: The Content-based Approach (Advances in Image Communication, Volume 7)
Furthermore, the segmentation algorithm becomes more robust. Coarse resolution images do not contain details, which means that in the beginning the segmentation is guided by dominant features of the image. The partitions will adapt to details only at finer resolutions. Multi-resolution approaches have proven to be particularly useful for segmentation of texture and high resolution images, where the information is spread over large areas [18, 68]. 4 Motion So far only still image segmentation has been considered in this chapter.
Canny considers a one-dimensional edge of known cross-section with additive white Gaussian noise. This one-dimensional signal is convolved with a filter so that the center of the edge corresponds to a local maximum in the filter output. The objective is now to find a filter that yields the best performance with respect to the three criteria. The optimal filters for different types of edges are derived using numerical optimization. Furthermore, it is shown that the impulse response of the optimal step edge operator can be approximated by the first derivative of a Gaussian function.
Pappas proposes an energy function U(X = x) with non-zero contributions coming only from two-point cliques. The clique potential Vc(x) associated with such pairs of horizontally, vertically, or diagonally adjacent pixels is given by -fl, Vc(x) - +fl, if x(i,j) - x(k, l) and (i, j), (k, l) e C if x(i, j) 7~ x(k, l) and (i, j), (k, l) E C. 39) Recall that a low potential or energy corresponds to a high probability and vice versa. By choosing a positive value for r two neighboring pixels (i, j) and (k, l) are assigned a higher probability if they belong to the same region.