By K.N. Ngan, T. Meier, D. Chai
Lately, the paradigm of video coding has shifted from that of a frame-based method of a content-based method, really with the finalization of the ISO multimedia coding commonplace, MPEG-4. MPEG-4 is the rising general 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 booklet addresses the tough challenge of video segmentation, and the extraction and monitoring of video item planes as outlined in MPEG-4. It then makes a speciality of the categorical factor of face segmentation and coding as utilized to videoconferencing with a view to enhance the standard of videoconferencing pictures specifically within the facial area.
Modal-based coding is a content-based coding method used to code man made gadgets that experience develop into a huge a part of video content material. It leads to super low bit premiums simply because in simple terms the parameters had to characterize the modal are transmitted. Model-based coding is integrated to supply historical past details for the artificial item coding in MPEG-4. finally, MPEG-4, the 1st coding ordinary for multimedia content material is defined intimately. the themes coated contain the coding of audio items, 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 normal. It serves as a superb 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
51) we obtain ! x --alx+a2y+a3 , y - - a 4 x + aSy + a6 with al - ( 8 1 1 - - 8 1 3 c ) ,a b and a5 - ( s 2 2 - 823c), affine motion model. ( 8 1 2 - 8 1 3 c ) , b a3 -- (tl 4 - 8 1 3 c )1, a4 -- (8 21 - - 8 23c), a -- (t2 + S23c). 4. 9: Projection of pixel (X, Y, Z) onto image plane (x, y) under perspective (central) projection. In the case of the more realistic perspective (central) p r o j e c t i o n it can be seen from Fig. 50) this results in the e i g h t - p a r a m e t e r m o d e l alx !
6: Optical flow constraint line. of the local image gradient can be derived from the OFC . This is also known as the aperture problem of motion estimation and is illustrated in Fig. 7. The true motion cannot be computed by considering just a small neighborhood. Instead, only the motion normal to the object contour is observable. Corners and regions with sufficient texture, however, are not affected by the aperture problem. 47) is, in the absence of additional constraints, a classical ill-posed problem .
To start with, the two most basic operators, erosion and dilation, will be introduced. Let B denote a window or flat structuring element and let Bx,v be the translation of B so that its origin is located at (x, y). Then, the erosion CB(I) of an image I by the structuring element B is defined as eB(I)(x,y) -- min (k,1)cB~,~ I(k, 1). 29) Similarly, the dilation 5B(I) of the image I by the structuring element B is given by 6 B ( I ) ( x , y) -- max (k,L)cB~,~ I(k, l). 30) 24 CHAPTER 1. IMAGE AND VIDEO SEGMENTATION For example, consider a window B consisting of 3 x 3 pixels.