Hierarchical GMM to handle sharp changes in moving object detection

Electronics Letters

Volumn 40, Issue 13, 2004, Pages 801-802

  Sun, Y ^a   Yuan, B ^a  

^a BEIJING JIAOTONG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CORRELATION METHODS; ESTIMATION; LIGHTING; ONLINE SYSTEMS; PROBABILITY; VECTORS;

GAUSSIAN MIXTURE MODELS (GMM); MOVING OBJECTS; OBJECT DETECTION;

OBJECT RECOGNITION;

EID: 3042732138     PISSN: 00135194     EISSN: None     Source Type: Journal    
DOI: 10.1049/el:20040552     Document Type: Article

References (4)

1. Stauffer, C., and Grimson, W.E.L.: 'Learning patterns of activity using real-time tracking', IEEE Trans. Pattern Anal. Mach. Intell., 2000, 22, pp. 747-57
2. Collins, R.T., Lipton, A.J., Fujiyoshi, H., and Kanade, T.: 'Algorithms for cooperative multisensor surveillance', Proc. IEEE, 2001, 89, (10), pp. 1456-1477
3. Stenger, B., Ramesh, V., Paragios, N., Coetzee, F., and Buhmann, J.M.: 'Topology free hidden Markov models: application to background modeling'. Proc. 8th IEEE Int. Conf. on Computer Vision. (ICCV 2001), Vancouver, BC, Canada, July 2001, Vol. 1, pp. 294-301
4. Kaewtrakulpong, P., and Bowden, R.: 'An improved adaptive background mixture model for realtime tracking with shadow detection'. Proc. 2nd European Workshop on Advanced Video Based Surveillance Systems, (AVBS01), London, UK, September 2001