Title :
Key Frame Extraction Based on Connectivity Clustering
Author :
Xiao, Yongliang ; Xia, Limin
Author_Institution :
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
Abstract :
Key frames play a very important role in video retrieval. In this paper, we introduce a novel method to extract key frames to represent video shot based on connectivity clustering. Compared with other methods, the proposed method can dynamically divide the frames into clusters depending on the content of shot, and then the frame closest to the cluster centroid is chosen as the key frame for the video shot. Experimental results and the comparisons with other methods on various types of video sequences illustrate the high performance of the proposed method.
Keywords :
image sequences; pattern clustering; video retrieval; connectivity clustering; key frame extraction; video retrieval; video shot; Clustering algorithms; Computer science; Computer science education; Data mining; Educational technology; Information management; Information retrieval; Information science; Pattern recognition; Video sequences; connectivity clustering; key frame; shot; video retrieval;
Conference_Titel :
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6388-6
Electronic_ISBN :
978-1-4244-6389-3
DOI :
10.1109/ETCS.2010.129