Improving the segmentation stage of a pedestrian tracking video-based system by means of evolution strategies

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3907 LNCS, Issue , 2006, Pages 438-449

  Perez O ^a   Patricio, M A ^a   Garcia J ^a   Molina, J M ^a  

^a UNIVERSIDAD CARLOS III DE MADRID   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE SEGMENTATION; PROBLEM SOLVING; TELEVISION EQUIPMENT; TRACKING (POSITION); VIDEO SIGNAL PROCESSING;

EVOLUTION STRATEGIES; MORPHOLOGICAL PROCESSES; POST-PROCESSING OPERATIONS; VIDEO SEQUENCES;

EVOLUTIONARY ALGORITHMS;

EID: 33745786044     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11732242_39     Document Type: Conference Paper

References (22)

1. th European Workshop on Evolutionary Computation in Image Analysis and Signal Processing. EvoIASP 2005. Lausanne, Switzerland (2005).
2. García, J. A. Besada, J. M. Molina, J. Portillo. Fuzzy data association for image-based tracking in dense scenarios, IEEE International Conference on Fuzzy Systems. Honolulu, Hawaii (2002)
3. Friedman, N. and Russell, S.: Image segmentation in video sequences: A probabilistic approach, in Proceedings of the Thirteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI 97), Morgan Kaufmann Publishers, Inc., (San Francisco, CA) (1997) 175-181.
4. Rosin, P.L., and Ellis, T.: Image Difference Threshold Strategies and Shadow Detection, in the 6th BMVC 1995 conf. proc., Birmingham, UK, (1995) 347-356.
5. Jiang, C.: Shadow identification, CVGIP: Image Understanding, 59(2) (1994) 213-225.
6. Prati, A., Mikic, I., Trivedi, M.M., Cucchiara, R.: Detecting Moving Shadows: Algorithms and Evaluation, IEEE Trans. PAMI 25(7) (2003) 918-923.
7. Bevilacqua, A.: Effective Shadow Detection in Traffic Monitoring Applications. WSCG 2003, 11(1)
8. Zhang, Y.J.: Evaluation and comparison of different segmentation algorithms, Pattern Recognition Letters 18 (1997) 963-974.
9. Chabrier, S., Emile, B., Laurent, H., Rosenberger, C.,March, P.: Unsupervised Evaluation of Image Segmentation Application to Multi-spectral Images. 17th International Conference on Pattern Recognition (ICPR'04) 1 (2004) 576-579.
10. Erdem, E., Sankur, B., Tekalp, A.M.: Metrics for performance evaluation of video object segmentation and tracking without ground-truth. ICIP 2 (2001) 69-72.
11. Pokrajac, D. and Latecki, L.J.: Spatiotemporal Blocks-Based Moving Objects Identification and Tracking. IEEE Int. W. Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS). Nice, France. (2003).
12. Black, J., Ellis, T., and Rosin, P.: A Novel Method for Video Tracking Performance Evaluation, Joint IEEE Int. Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VS-PETS). Nice, France. (2003).
13. Aggarwal, J.K. and Cai, Q.: Human motion analysis: A review. Computer Vision and Image Understanding, 73(3) (1999) 428-440.
14. Wang, L., Hu, W., and Tan., T.: Recent developments in human motion analysis. Pattern Recognition, 36(3) (2003) 585-601.
15. Haritaoglu, D.I., Harwood, D., and Davis, L.: W4: Real- Time Surveillance of People and Their Activities, IEEE Trans. Pattern Analysis and Machine Intelligence 22(8) (2000) 809-830.
16. Remagnino, P., Jones, G.A., Paragios, N., and Regazzoni, C.S.: Video-Based Surveillance Systems. Kluwer Academic Publishers, 2002.
17. Wren, C., Azarbayejani, A., Darrell, T., and Pentland, A.P.: Pfinder: Real-time Tracking of the Human Body, IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI) 19(7) (1997) 780-785.
18. Stauffer, C., and Grimson, W.: Adaptive background mixture models for realtime tracking. In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (1999) 246-252.
19. Lipton, A.J., Fujiyoshi, H., and Patil, R.S.: Moving target classification and tracking from real-time video. In Proc. of Workshop Applications of Computer Vision, (1998) 129-136.
20. Cohen, I., and Medioni, G.: Detecting and Tracking Moving Objects in Video from an Airborne Observer, Proc. IEEE Image Understanding Workshop, (1998) 217-222.
21. Kim, E.Y., Park, S.H., Hwang, S., and Kim, H.J.: Video Sequence Segmentation Using Genetic Algorithms. Pattern Recognition Letter, 23(7) (2002) 843-863.
22. Hwang, S., Kim, E.Y., Park, S.H., and Kim, H.J.: Object Extraction and Tracking Using Genetic Algorithms, in Proc. IEEE Signal Processing Society ICIP 2 (2001) 383-386.