Traffic Video Segmentation and Key Frame Extraction Using Improved Global K-Means Clustering

摘要：

Huge am ount of Traffic video segmented into manageable shots is the key step of database storage and video analysis in Intelligent Transportation Systems (ITS). Then key frames are extracted for representing main visual content of each shot. This paper proposes a novel approach for the segmentation of traffic video by the judgment of motion trend and supported by the vehicle status changes. Considering the number of sub-shots in shots as the initialized clusters number, we apply an improved global k-means clustering algorithm to extract the key frame. With the numerical experiments on traffic surveillance video using the propose method in this paper, shot boundary detection can be made in an effective manner. The extracted key frames by our approach also show better representation for the visual content of the video shot compared with other methods.

关键词： traffic video shot segmentation global K-means key frame

作者: Yuanfeng Yang Zhiming Cui Jian Wu Guangming Zhang Xuefeng Xian

作者单位: The Institute of Intelligent Information Processing and Application, Soochow University, Suzhou, Chi The Institute of Intelligent Information Processing and Application, Soochow University, Suzhou, Chi The Institute of Intelligent Information Processing and Application, Soochow University, Suzhou, Chi The Institute of Intelligent Information Processing and Application, Soochow University, Suzhou, Chi

会议类型: 国际会议

会议名称: Third International Symposium on Information Science and Engineering(第三届信息科学与工程国际会议 ISISE 2010)

会议地点: 上海

会议语种:英文

页码: 521-525

在线出版日期: 2010-12-24（万方平台首次上网日期，不代表论文的发表时间）