Title :
Appearance based tracking with background subtraction
Author :
Jayamanne, Dileepa Joseph ; Samarawickrama, Jayathu ; Rodrigo, Ranga
Author_Institution :
Electron. & Telecommun. Eng., Univ. of Moratuwa, Moratuwa, Sri Lanka
Abstract :
Grouping the detected feature points traditionally requires the storage of long corner tracks. The traditional method does not permit to arrive at a decision to cluster the feature points based on a frame by frame basis. This paper presents a method to group the feature points directly into objects using the most recent 20 frames. The detected corner features are validated and clustered based on two approaches. When objects move in isolation, an EM algorithm is used to cluster and every object is detected and tracked. When objects move under partial occlusion, the corner features are clustered based on an agglomerative hierarchical clustering approach. A probabilistic framework has also been applied to determine the object level membership of the candidate corner features. A novel foreground estimation algorithm with an accuracy of 98% based on color information, background subtraction result and detected corner features is also presented.
Keywords :
expectation-maximisation algorithm; feature extraction; image colour analysis; object tracking; pattern clustering; EM algorithm; agglomerative hierarchical clustering approach; appearance based tracking; background subtraction; candidate corner features; color information; corner tracks; detected feature points; feature points clustering; foreground estimation algorithm; object level membership; probabilistic framework; Computers;
Conference_Titel :
Computer Science & Education (ICCSE), 2013 8th International Conference on
Conference_Location :
Colombo
Print_ISBN :
978-1-4673-4464-7
DOI :
10.1109/ICCSE.2013.6553988