Title :
Keyframe extraction based on kmeas results to adjacent DC images similarity
Author :
Shi, Fangxia ; Guo, Xiaojun
Author_Institution :
Sch. of Inf. Eng., Tibet Nat. Inst., Xianyang, China
Abstract :
Keyframe extraction is the fundamental process of video content analysis, retrieval and so on. For extracting keyframe from video compressed stream efficiently, this paper presents an useful and fast method. It firstly computes the similarity set of adjacent I frames´ DC images, secondly uses kmeans algorithm to cluster the similarity set, and finally selects keyframes based on the clustering results. The experiment results show that our method is able to get proper keyframes from test video files and finish keyframe extraction in much less time.
Keywords :
data compression; video coding; adjacent DC images similarity; clustering results; keyframe extraction; kmeas results; test video files; video compressed stream; video content analysis; Clustering algorithms; Conferences; Data mining; Feature extraction; Image coding; Silicon; Streaming media; DC image; keyframe extraction; kmeans; video compressed stream;
Conference_Titel :
Signal Processing Systems (ICSPS), 2010 2nd International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-6892-8
Electronic_ISBN :
978-1-4244-6893-5
DOI :
10.1109/ICSPS.2010.5555457