Fusion of motion segmentation with online adaptive neural classifier for robust tracking

VISAPP 2009 - Proceedings of the 4th International Conference on Computer Vision Theory and Applications

Volumn 2, Issue , 2009, Pages 410-416

  Slawomir, B ^a   Suresh, Sunclaram ^b   Bremonci, Francois ^b   Thonnat, Monique ^b  

^a POZNAN UNIVERSITY OF TECHNOLOGY   (Poland)

^b PULSAR group 2004 ^*  (France)

Author keywords

Feature extraction; Gaussian activation function; Motion segmentation; Neural network; Object tracking; On line learning; Reliability classification

Indexed keywords

BACKGROUND REGION; GAUSSIAN ACTIVATION FUNCTION; ILLUMINATION VARIATION; MOTION SEGMENTATION; NEURAL CLASSIFIERS; OBJECT CLASSIFICATION; OBJECT TRACKING; ON-LINE LEARNING; ROBUST TRACKING; VIDEO SEQUENCES;

CLASSIFIERS; COMPUTER VISION; LEARNING SYSTEMS; NEURAL NETWORKS; VIDEO RECORDING;

FEATURE EXTRACTION;

EID: 70349290687     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Avidan, S. (2007). Ensemble tracking. IEEE Trans. Pattern Anal. Machine Intell., 29(2):261-271. (Pubitemid 46420886)
2. Bk, S., Suresh, S., Bremond, F., and Thonnat, M. (2008). Fusion of motion segmentation and learning based tracker for visual surveillance. In Internal report: INRIA Sophia Antipolis, http:llwwwsop.inria.fr/pulsar/personnel/ Francois.Bremond/topicsText/neuraiProject.html, volume 1, pages 1-10.
3. Collins, R. T., Liu, Y., and Leordeanu, M. (2005). Online selection of discriminative tracking features. IEEE Trans. Pattern Anal. Machine Intell., 27(l0):1631-1643. (Pubitemid 41555407)
4. Cootes, T., Edwards, G., and Taylor, C. (2001). Active appearance models. IEEE Trans. Pattern Anal. Machine Intell., 25(5):681-685. (Pubitemid 32585279)
5. Jepson, A. D., Fleet, D. J., and El-Maraghi, T. (2003). Robust online appearance model for visual tracking. IEEE Trans. Pattern Anal. Machine Intell., 25( 10): 1296-1311.
6. Nummiaro, K., Koller-Meier, F., and Van Gool, L. (2003). An adaptive color-based particle filter. Image vision computing, 21(1):99-110.
7. Stauffer, C. and Brady, J. (2000). Learning patterns of activity using real-time tracking. IEEE Trans. Pattern Anal. Machine Intell., 22(8):747-757. (Pubitemid 30941143)
8. Suresh, S., Sundararajan, N., and Saratchandran, P. (2008a). Risk sensitive loss functions for sparse multi-category classification problems. Information Sciences, 178(12):2621-2638.
9. Suresh, S., Sundararajan, N., and Saratchandran, P. (2008b). A sequential multi-category classifier using radial basis function networks. Neurocomputing, 71(7-9):1345-1358.
10. Williams, O., Blake, A., and Cipolla, R. (2005). Sparse bayesian learning for efficient visual tracking. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 27(8):1292-1304. (Pubitemid 41245058)
11. Yilmaz, A., Javed, O., and Shah, M. (2006). Object tracking: A survey. ACM Computing Surveys, 38(4):1-45. (Pubitemid 46041487)
12. Zouba, N., Boulay, B., Brethond, F., and Thonnat, M. (2008). Monitoring activities of daily living (adls) of elderly based on 3d key human postures. In Proc. of International Cognitive Vision Workshop, pages xx-xx, Greece.
13. Züfliga, M., Brémond, F., and M.Thonnat (2006). Fast and reliable object classification in video based on a 3d generic model. In Proceedings of the International Conference on Visual Information Engineering (V1E2006), pages 433-440, Bangalore, India.