The h.264 advanced video coding (h.264/AVC) standard provides several advanced features such as improved coding efficiency and error robustness for video storage and transmission. In order to improve the coding perfor...
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The h.264 advanced video coding (h.264/AVC) standard provides several advanced features such as improved coding efficiency and error robustness for video storage and transmission. In order to improve the coding performance of h.264/AVC, coding control parameters such as group-of-pictures (GOP) sizes should be adaptively adjusted according to different video content variations (VCVs), which can be extracted from temporal deviation between two consecutive frames. The authors present a simple VCV estimation to design adaptive GOP detection (AGD) and scene change detection (SCD) methods by using the obtained motion information, where the motion vectors and the sum of absolute transformed differences as VCV features are effectively used to design the AGD and SCD algorithms, respectively. In order to avoid unnecessary computation, the above VCV features are obtained only in the 4 x 4 inter-frame prediction mode. Simulation results show that the proposed AGD with SCD methods can increase the peak signal-to-noise ratio by 0.62 dB on average over the h.264/AVC operated with a fixed GOP size. Besides, the proposed SCID method can reach a scene change detection rate of 98%.
The h.264videocoding standard achieves high performance compression and image quality at the expense of increased encoding complexity. Consequently, several fast mode decision and motion estimation techniques have b...
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The h.264videocoding standard achieves high performance compression and image quality at the expense of increased encoding complexity. Consequently, several fast mode decision and motion estimation techniques have been developed to reduce the computational cost. These approaches successfully reduce the computational time by reducing the image quality and/or increasing the bitrate. In this paper we propose a novel fast mode decision and motion estimation technique. The algorithm utilizes preprocessing frequency domain motion estimation in order to accurately predict the best mode and the search range. Experimental results show that the proposed algorithm significantly reduces the motion estimation time by up to 97%, while maintaining similar rate distortion performance when compared to the Joint Model software. C (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3597609]
This paper presents a real-time segmentation algorithm to obtain moving objects from the h.264 compressed domain. The proposed segmentation works with very little information and is based on two features of the h.264 ...
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This paper presents a real-time segmentation algorithm to obtain moving objects from the h.264 compressed domain. The proposed segmentation works with very little information and is based on two features of the h.264 compressed video: motion vectors associated to the macroblocks;and decision modes. The algorithm uses fuzzy logic and allows to describe position, velocity and size of the detected regions in a comprehensive way, so the proposed approach works with low level information but manages highly comprehensive linguistic concepts. The performance of the algorithm is improved using dynamic design of fuzzy sets that avoids merge and split problems. Experimental results for several traffic scenes demonstrate the real-time performance and the encouraging results in diverse situations. Crown Copyright (C) 2009 Published by Elsevier Inc. All rights reserved.
This paper presents a real-time segmentation algorithm to obtain moving objects from the h.264 compressed domain. The proposed segmentation works with very little information and is based on two features of the h.264 ...
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ISBN:
(纸本)9789899507968
This paper presents a real-time segmentation algorithm to obtain moving objects from the h.264 compressed domain. The proposed segmentation works with very little information and is based on two features of the h.264 compressed video: motion vectors associated to the macroblocks and decision modes. The algorithm uses fuzzy logic and allows to describe position, velocity and size of the detected regions in a comprehensive way, so the proposed approach works with low level information but manages highly comprehensive linguistic concepts. The performance of the algorithm is improved using dynamic design of fuzzy sets that avoids merge and split problems. Experimental results for several traffic scenes demonstrate the real-time performance and the encouraging results in diverse situations.
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