BEHAVIOR KEY FRAME EXTRACTION USING INVARIANT MOMENT AND UNSUPERVISED CLUSTERING

摘要：

Key frame extraction technique plays an important role in video analysis and content-based video retrieval. Key frame has been used to reduce the use of video indexing data greatly and it also provides a framework to video summaries and retrieval. This paper proposes a novel method based on invariant moments for key frame extraction, according to the changes of independent objects shape and brightness. We first extract a moving object from the video sequence and compute the invariant moments in the area. Then cluster consecutive frames of similar invariant moments by unsupervised clustering. Finally, extract the typical data from each cluster as the key frame. The experimental results of different scenes show the feasibility of this method.

关键词： Video Retrieval Key Frame Invariant Moment Unsupervised Clustering

作者: YANG PENG JIHONG PEI YANG XUAN

作者单位: College of Information Engineering, Shenzhen University, Shenzhen, 518060, China Intelligent Information Processing Laboratory of Shenzhen University, Shenzhen, 518060.China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2503-2508

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）