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 strategy, quite with the finalization of the ISO multimedia coding regular, MPEG-4. MPEG-4 is the rising common for the coding of multimedia content material. It defines a syntax for a suite of content-based functionalities, specifically, content-based interactivity, compression and common entry. despite the fact that, 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 e-book 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 explicit factor of face segmentation and coding as utilized to videoconferencing so that it will enhance the standard of videoconferencing photographs particularly within the facial area.
Modal-based coding is a content-based coding approach used to code man made items that experience turn into a major a part of video content material. It leads to tremendous low bit premiums simply because purely the parameters had to symbolize the modal are transmitted. Model-based coding is incorporated to supply heritage details for the substitute 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 gadgets, the coding of average and artificial video items, and mistake resilience.
Advanced Video Coding is without doubt one of the first books on content-based coding and MPEG-4 coding commonplace. It serves as an outstanding details resource and reference for either researchers and working towards engineers.
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Additional info for Advanced Video Coding: Principles and Techniques, Volume 7: The Content-based Approach
This book will concentrate on two approaches which have grown in popularity over the last few years; these are morphological and Bayesian segmentation. They both have in common that they are based on a sound theory. Morphology refers to a branch of biology that is concerned with the form and structure of animals and plants. In image processing and computer vision, mathematical morphology denotes the study of topology and structure of objects from images. It is also known as a shape-oriented approach to image processing, in contrast to, for example, frequency-oriented approaches.
The marker extraction step often contains most of the know-how of the segmentation algorithm . Both the simplification filters and the watershed algorithm are clearly specified, apart from the choice of some parameters, whereas the marker extraction process will depend on a particular application. For instance, Fig. 4 demonstrated that morphological opening-closing 4Recall that the dilation operator has the effect of increasing gray values. 3. 5: The watershed algorithm owes its name to the relief interpretation of the gradient image.
The choice of the annealing schedule is enormously important. If the temperature T is decreased suiticiently slowly, the Gibbs sampler will be able to reach the global minimum. 11) with the constant Tmax, then the solution X (n) after the nth iteration will converge to the global minimum as n --+ oc. Should there be multiple minima, x (n) will be uniformly distributed over those values of X that take on the global minimum. Notice that the constant Tmax must be selected appropriately . 11) is normally too slow for practical applications.