Show simple item record Jayamanne, DJ Samarawickrama, J Rodrigo, R 2018-11-07T18:57:21Z 2018-11-07T18:57:21Z
dc.description.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. en_US
dc.language.iso en en_US
dc.title Appearance based tracking with background subtraction en_US
dc.type Conference-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Department of Electronic and Telecommunication Engineering en_US
dc.identifier.year 2013 en_US
dc.identifier.conference 8th International Conference on Computer Science & Education - (ICCSE - 2013) en_US Colombo en_US
dc.identifier.pgnos pp. 643 - 649 en_US en_US en_US en_US

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