Moving Object Extraction Using Compressed Domain Features of H.264 INTRA Frames

Fu-Ping Wang, W. Chung, Guo-Kai Ni, Ing-Yi Chen, S. Kuo
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引用次数: 3

Abstract

A new efficient algorithm using the compressed domain features of H.264 INTRA frames is proposed for moving object extraction on huge video surveillance archives. To achieve searching efficiency, we propose to locate moving objects by scrutinizing only the INTRA frames in video surveillance archives in H.264 compressed domain with short GOP length. In the proposed structure, a modified codebook algorithm is designed to build the block-based background models from the INTRA coding features. Through the subtraction with the background codebook models, the foreground energy frame is filtered and normalized for detecting the existence of moving objects. To overcome the over-segmentation problem and enable the unsupervised searching, a new structure of hysteresis thresholding, where the thresholds are obtained automatically by an efficient algorithm, is adopted to extract foreground blocks. At the final step, the connected components labeling (CCL) and morphological filters are employed to obtain the list of moving objects. As shown in the experimental results, the proposed algorithm outperforms representative existing works.
利用H.264 INTRA帧压缩域特征提取运动目标
提出了一种利用H.264 INTRA帧压缩域特征提取海量视频监控档案中运动目标的高效算法。为了提高搜索效率,我们提出在H.264压缩域中,仅对GOP长度较短的视频监控档案中的INTRA帧进行定位。在该结构中,设计了一种改进的码本算法,利用INTRA编码特征构建基于块的背景模型。通过与背景码本模型的相减,对前景能量帧进行滤波和归一化,检测运动目标的存在。为了克服过度分割问题和实现无监督搜索,采用一种新的迟滞阈值结构提取前景块,该结构通过一种高效的算法自动获得阈值。最后,采用连接分量标记(CCL)和形态滤波器获得运动目标列表。实验结果表明,本文提出的算法优于已有代表性的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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