Adaptive feature-based motion analysis and its application to interframe coding
Contemporary methods of interframe coding use motion estimation and compensation as a means of reducing the prediction error in algorithms which provide a large reduction in data rate. These methods can broadly be divided into two categories, pel recursive and block matching algorithms. Further work...
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| Vydané v: | Fifth International Conference on Image Processing and its Applications s. 31 - 35 |
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| Hlavní autori: | , |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
London
IEE
1995
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| ISBN: | 0852966423, 9780852966426 |
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| Abstract | Contemporary methods of interframe coding use motion estimation and compensation as a means of reducing the prediction error in algorithms which provide a large reduction in data rate. These methods can broadly be divided into two categories, pel recursive and block matching algorithms. Further work has investigated model-based coding, using the displacement and deformation of image objects as the criteria for interframe coding. Consideration of a typical audio-visual scene indicates that a motion search of the entire image is unnecessary, since motion is mainly concentrated in the detailed area around the subject's face. The technique described can be considered as a step between the simple full-search block matching method and the more involved approach of model-based coding. It is demonstrated that, using a low-resolution image, objects can be segmented into features of consistent texture, small enough to provide interframe detail and large enough to provide the basis of an algorithm of low complexity and real-time processing potential. |
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| AbstractList | Contemporary methods of interframe coding use motion estimation and compensation as a means of reducing the prediction error in algorithms which provide a large reduction in data rate. These methods can broadly be divided into two categories, pel recursive and block matching algorithms. Further work has investigated model-based coding, using the displacement and deformation of image objects as the criteria for interframe coding. Consideration of a typical audio-visual scene indicates that a motion search of the entire image is unnecessary, since motion is mainly concentrated in the detailed area around the subject's face. The technique described can be considered as a step between the simple full-search block matching method and the more involved approach of model-based coding. It is demonstrated that, using a low-resolution image, objects can be segmented into features of consistent texture, small enough to provide interframe detail and large enough to provide the basis of an algorithm of low complexity and real-time processing potential. |
| Author | Ibrahim, M.K Garnham, N.W |
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| Keywords | low complexity algorithm image classification adaptive feature-based motion analysis prediction error reduction data rate reduction block matching algorithms image matching image texture motion compensation pel recursive algorithms full-search block matching method motion search adaptive signal processing image segmentation real-time processing interframe coding motion estimation image displacement audio-visual scene model-based coding image deformation image coding image resolution low-resolution image |
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| Snippet | Contemporary methods of interframe coding use motion estimation and compensation as a means of reducing the prediction error in algorithms which provide a... |
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| SubjectTerms | Codes Optical information, image and video signal processing Pattern recognition |
| Title | Adaptive feature-based motion analysis and its application to interframe coding |
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