[1] PETS: Performance Evaluation
of Tracking and Surveillance.
http://www.cvg.rdg.ac.uk/slides/pets.html.
[2] A. Alahi, L. Jacques, Y. Boursier, and P. Vandergheynst.
Sparity-driven people localization algorithm:
Evaluation in crowded scenes environments. In
Twelfth IEEE InternationalWorkshop on Performance
Evaluation of Tracking and Surveillance, 2009.
[3] A. Albiol, M. J. Silla, A. Albiol, and J. M. Mossi.
Video analysis using corners motion analysis. In
Eleventh IEEE International Workshop on Performance
Evaluation of Tracking and Surveillance, pages
31–37, 2009.
[4] D. Arsic, A. Lyutskanov, G. Rigoll, and B. Kwolek.
Multi camera person tracking applying a graph-cuts
based foreground segmentation in a homography
framework. In Twelfth IEEE International Workshop
on Performance Evaluation of Tracking and Surveillance,
2009.
[5] L. Bazzani, D. Bloisi, and V. Murino. A comparison
of multi hypothesis kalman filter and particle filter for
multi-target tracking. In Eleventh IEEE International
Workshop on Performance Evaluation of Tracking and
Surveillance, 2009.
[6] J. Berclaz, F. Fleuret, and P. Fua. Multiple object
tracking using flow linear programming. In Twelfth IEEE International Workshop on Performance Evaluation
of Tracking and Surveillance, 2009.
[7] J. Berclaz, A. Shahrokni, F. Fleuret, J. M. Ferryman,
and P. Fua. Evaluation of probabilistic occupancymap
people detection for surveillance systems. In Eleventh
IEEE International Workshop on Performance Evaluation
of Tracking and Surveillance, pages 55–62,
2009.
[8] D. Bolme, Y. Lui, B. Draper, and J. Beveridge. Simple
real-time human detection using a single correlation
filter. In Twelfth IEEE InternationalWorkshop on
Performance Evaluation of Tracking and Surveillance,
2009.
[9] M. D. Breitenstein, F. Reichlin, B. Leibe, E. Koller-
Meier, and L. van Gool. Markovian tracking-bydetection
from a single, uncalibrated camera. In
Eleventh IEEE International Workshop on Performance
Evaluation of Tracking and Surveillance, pages
71–78, 2009.
[10] A. B. Chan, M. Morrow, and N. Vasconcelos. Analysis
of crowded scenes using holistic properties. In
Eleventh IEEE International Workshop on Performance
Evaluation of Tracking and Surveillance, pages
101–108, 2009.
[11] S. Choudri, J. Ferryman, and A. Badii. Robust background
model for pixel based people counting. In
Twelfth IEEE InternationalWorkshop on Performance
Evaluation of Tracking and Surveillance, 2009.
[12] J.Ferryman and A. Shahrokni. An overview of the
pets2009 dataset. In Twelfth IEEE InternationalWorkshop
on Performance Evaluation of Tracking and
Surveillance, 2009.
[13] R. Kasturi, D. Goldgof, P. Soundararajan, V. Manohar,
J. Garofolo, R. Bowers, M. Boonstra, V. Korzhova,
and Jing Zhang. Framework for performance evaluation
of face, text, and vehicle detection and tracking
in video: Data, metrics, and protocol. Pattern Analysis
and Machine Intelligence, IEEE Transactions on,
31(2):319–336, Feb. 2009.
[14] N. Lehment, D. Arsic, A. Lyutskanov, B. Schuller, and
G. Rigoll. Statistical filters for crowd image analysis.
In Twelfth IEEE International Workshop on Performance
Evaluation of Tracking and Surveillance, 2009.
[15] P. K. Sharma, C. Huang, and R. Nevatia. Evaluation
of people tracking, counting and density estimation
in crowded environments. In Eleventh IEEE International
Workshop on Performance Evaluation of Tracking
and Surveillance, pages 39–46, 2009.
[16] J. Yang, Z. Shi, P. Vela, and J. Teizer. Probabilistic
multiple people tracking through complex situations.
In Eleventh IEEE International Workshop on Performance
Evaluation of Tracking and Surveillance, pages
79–86, 2009.