Adaptive online performance evaluation of video trackers

IEEE Transactions on Image Processing

Volumn 21, Issue 5, 2012, Pages 2812-2823

  SanMiguel, Juan C ^a   Cavallaro, Andrea ^b   Martínez, José M ^a  

^a UNIVERSIDAD AUTÓNOMA DE MADRID   (Spain)

^b QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

Failure detection; particle filter; time reversibility; track quality; tracking uncertainty; video tracking

Indexed keywords

FAILURE DETECTION; PARTICLE FILTER; TIME REVERSIBILITIES; TRACK QUALITY; TRACKING UNCERTAINTY; VIDEO TRACKING;

ERRORS; NONLINEAR FILTERING; RECOVERY; VIDEO RECORDING;

UNCERTAINTY ANALYSIS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; METHODOLOGY; PHOTOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING; VIDEORECORDING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; PHOTOGRAPHY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; VIDEO RECORDING;

EID: 84860179164     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2011.2182520     Document Type: Article

References (35)

1. E. Maggio and A. Cavallaro, Video Tracking: Theory and Practice. Hoboken, NJ: Wiley, 2011.
2. R. Kasturi, D. Goldgof, P. Soundararajan, V. Manohar, J. Garofolo, R. Bowers, M. Boonstra, V. Korzhova, and J. Zhang, "Framework for performance evaluation of face, text, and vehicle detection and tracking in video: Data, metrics, and protocol," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 2, pp. 319-336, Feb. 2008.
3. J. Black, T. Ellis, and P. Rosin, "A novel method for video tracking performance evaluation," in Proc. IEEE Int. Workshop Perform. Eval. Track. Surveill., Nice, France, Oct. 11-12, 2003, pp. 125-132.
4. D. Chau, F. Bremond, and M. Thonnat, "Online evaluation of tracking algorithm performance," in Proc. Int. Conf. Imag. Crime Prevention Detection, London, U.K., Dec. 3, 2009, pp. 1-6.
5. H. Wu, A. Sankaranarayanan, and R. Chellappa, "Online empirical evaluation of tracking algorithms," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 8, pp. 1443-1458, Aug. 2010.
6. N. Vaswani, "Additive change detection in nonlinear systems with unknown change parameters," IEEE Trans. Signal Process., vol. 55, no. 3, pp. 859-872, Mar. 2007.
7. E. Maggio, F. Smerladi, and A. Cavallaro, "Adaptive multifeature tracking in a particle filtering framework," IEEE Trans. Circuits Syst. Video Technol., vol. 17, no. 10, pp. 1348-1359, Oct. 2007.
8. F. Van der Heijen, "Consistency checks for particle filters," IEEE Trans. Pattern Anal. Mach. Intell., vol. 1, no. 1, pp. 140-145, Jan. 2006.
9. C. Erdem, Sankur, and A. Tekalp, "Performance measures for video object segmentation and tracking," IEEE Trans. Image Process., vol. 13, no. 7, pp. 937-951, Jul. 2004.
10. R. Collins, Y. Liu, and M. Leordeanu, "Online selection of discriminative tracking features," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 10, pp. 1631-1643, Oct. 2005.
11. Z. Kalal, K. Mikolajczyk, and J. Matas, "Forward-backward error: Automatic detection of tracking failures," in Proc. IEEE Int. Conf. Pattern Recogn., Istanbul, Turkey, Aug. 23-26, 2010, pp. 2756-2759.
12. J. SanMiguel, A. Cavallaro, and J. Martinez, "Evaluation of online quality estimators for video object tracking," in Proc. IEEE Int. Conf. Image Process., Hong Kong, China, Sep. 26-29, 2010, pp. 4657-4660.
13. C. Piciarelli, G. Foresti, and L. Snidaro, "Trajectory clustering and its applications for video surveillance," in Proc. IEEE Adv. Video-Based Signal Surveill., Como, Italy, Sep. 15-16, 2005, pp. 40-45.
14. D. Hall, "Automatic parameter regulation of perceptual systems," Image Vis. Comput., vol. 24, no. 8, pp. 870-881, Aug. 2006.
15. H. Wu and Q. Zheng, "Self-evaluation of visual tracking systems," in Proc. Army Sci. Conf., Orlando, FL, Nov. 29-Dec., 2, 2004.
16. A. Doulamis, "Dynamic tracking re-adjustment: A method for automatic tracking recovery in complex visual environments," Multimedia Tools Appl., vol. 50, no. 1, pp. 49-73, Jan. 2010.
17. E. Polat, M. Yeasin, and R. Sharma, "Tracking body parts of multiple people: A new approach," in Proc. IEEE Workshop Multi-Object Track., Vancouver, BC, Canada, Jul. 8, 2001, pp. 35-42.
18. R. Liu, S. Li, X. Yuan, and R. He, "Online determination of track loss using template inverse matching," in Proc. Int.Workshop Vis. Surveill., Marseille, France, Oct. 17, 2008.
19. P. Pan, F. Porikli, and D. Schonfeld, "Recurrent tracking using multifold consistency," in Proc. IEEE Int. Workshop Perform. Eval. Track. Surveill., Miami, FL, Jun. 20-25, 2009.
20. Z. Han, Q.Ye, and J. Jiao, "Online feature evaluation for object tracking using Kalman filter," in Proc. IEEE Int. Conf. Pattern Recogn., Tampa, FL, Dec. 8-11, 2008, pp. 1-4.
21. C. Erdem, A. Tekalp, and B. Sankur, "Video object tracking with feedback of performance measures," IEEE Trans. Circuits Syst. Video Technol., vol. 4, no. 4, pp. 310-324, Apr. 2004.
22. P. Correia and F. Pereira, "Stand-alone object segmentation quality evaluation," EURASIP J. Appl. Signal Process., vol. 202, no. 4, pp. 389-400, Apr. 2002.
23. C. Motamed, "Motion detection and tracking using belief indicators for an automatic visual-surveillance system," Image Vis. Comput., vol. 24, no. 11, pp. 1192-1201, Nov. 2006.
24. K. Nickels and S. Hutchinson, "Estimating uncertainty in SSD-based feature tracking," Image Vis. Comput., vol. 20, no. 1, pp. 47-58, Jan. 2002.
25. E. Loutas, I. Pitas, and C. Nikou, "Entropy-based metrics for the analysis of partial and total occlusion in video object tracking," Proc. Inst. Elect. Eng.-Vis., Image, Signal Process., vol. 151, no. 6, pp. 487-497, Dec. 2004.
26. L. Lu, X. Dai, and G. Hager, "A particle filter without dynamics for robust 3-D face tracking," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recogn. Workshop, Washington, DC, Jun. 27-Jul., 2, 2004, vol. 5, pp. 70-73.
27. V. Badrinarayanan, P. Perez, F. Le Clerc, and L. Oisel, "On uncertainties, random features and object tracking," in Proc. IEEE Int. Conf. Image Process., San Antonio, TX, Sep. 16-19, 2007, pp. 61-64.
28. A. Bagdanov, A. Del-Bimbo, F. Dini, and W. Nunziati, "Adaptive uncertainty estimation for particle filter-based trackers," in Proc. Int. Conf. Image Anal. Process., Modena, Italy, Sep. 10-14, 2007, pp. 331-336.
29. V. Badrinarayanan, P. Perez, F. Le Clerc, and L. Oisel, "Probabilistic color and adaptive multi-feature tracking with dynamically switched priority between cues," in Proc. IEEE Int. Conf. Comput. Vis., Rio de Janeiro, Brazil, Oct. 14-21, 2007, pp. 1-8.
30. R. M. Powers and L. Y. Pao, "Power and robustness of a track-loss detector based on Kolmogorov-Smirnov tests," in Proc. Amer. Control Conf., Minneapolis, MN, Jun. 14-16, 2006, pp. 3757-3764.
31. P. Pan, F. Porikli, and D. Schonfeld, "A new method for tracking performance evaluation based on reflective model and perturbation analysis," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., Taipei, Taiwan, Apr. 19-24, 2009, pp. 3529-3532.
32. K. Nummiaro, E. Koller-Meier, and E. Van Gool, "An adaptive colorbased particle filter," Image Vis. Comput., vol. 21, no. 1, pp. 99-110, Jan. 2003.
33. A. Nghiem, F. Bremond, M. Thonnat, and V. Valentin, "ETISEO, performance evaluation for video surveillance systems," in Proc. IEEE Conf. Adv. Video Signal Based Surveill., London, U.K., Sep. 5-7, 2007, pp. 476-481.
34. P. Chen and P. Popovich, Correlation: Parametric and Nonparametric Measures. Thousand Oaks, CA: Sage, 2002.
35. N. Vaswani and R. Chellappa, "A particle filtering approach to abnormality detection in nonlinear systems and its application to abnormal activity detection," in Proc. Int. Workshop Stat. Comput. Theories Vis., Nice, France, Oct. 13-16, 2003, pp. 1-8.