Title :
Moving target detection based on Genetic K-means Algorithm
Author :
Xiuman, Duan ; Guoxia, Sun ; Tao, Yang
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
Abstract :
Recently, the research on extracting moving objects from video sequences in the current computer vision applications is very popular. A new method based on genetic k-means algorithm from Gaussian mixture model (GMM) to deal with moving target of video image was purposed in this paper. The described method in this paper is learned from clustering idea, which is very different from traditional way. According to Genetic K-means Algorithm, by clustering of pixels on the timeline, the background could be described through several clusters. On the basic of these clusters, moving target detection could be done. Simulation experiment showed that the method could give a good result for the moving target detection.
Keywords :
Gaussian processes; computer vision; object detection; GMM; Gaussian mixture model; computer vision; genetic K-means algorithm; moving target detection; target detection moving; Biological cells; Clustering algorithms; Computational modeling; Computer vision; Genetics; Object detection; Vectors; background modeling; genetic k-means algorithm; moving target detection;
Conference_Titel :
Communication Technology (ICCT), 2011 IEEE 13th International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-61284-306-3
DOI :
10.1109/ICCT.2011.6157992