DocumentCode
2540872
Title
Study on subtractive clustering video moving object locating method with introduction of eigengap
Author
Sun, Zhi-hai ; Zhou, Wen-hui ; Li, Er-tao ; Zhang, Hua
Author_Institution
Coll. of Comput. Sci., Hangzhou Dianzi Univ., Hangzhou, China
fYear
2012
fDate
29-31 May 2012
Firstpage
609
Lastpage
612
Abstract
Considering the problem that the iteration number of video moving object locating method based on subtractive clustering existing a lot of uncertainties, a new video moving object locating method based on subtractive clustering introducing eigengap was proposed. Considering the data density function of subtractive clustering method, affinity matrix and the diagonal matrix was constructed, then eigenvalue and eigengap were both computed using normalized affinity matrix, the iteration number of subtractive clustering video moving object locating method could be automatically determined using the first maximum eigengap value. The extraordinary feature of proposed method was that the affinity matrix and the diagonal matrix could be both determined while computing density value, and then the iteration number could be automatically determined using eigengap. Experiment results showed that the proposed method had a better performance on dealing with the iteration number of subtractive clustering locating method.
Keywords
data handling; eigenvalues and eigenfunctions; iterative methods; matrix algebra; object detection; pattern clustering; video signal processing; affinity matrix; data density function; diagonal matrix; eigengap introduction; extraordinary feature; iteration number; maximum eigengap value; normalized affinity matrix; subtractive clustering; subtractive clustering video moving object locating method; Classification algorithms; Clustering algorithms; Educational institutions; Eigenvalues and eigenfunctions; Road transportation; Software algorithms; Sun; affinity matrix; eigengap; high dynamic range scenes; subtractive clustering; video moving object locating;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location
Sichuan
Print_ISBN
978-1-4673-0025-4
Type
conf
DOI
10.1109/FSKD.2012.6233715
Filename
6233715
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