@INPROCEEDINGS{PitieICIP05, 
author= {F. Piti\'{e}  and S. A. Berrani and A. Kokaram and R. Dahyot}, 
booktitle= {IEEE International Conference on Image Processing 2005}, 
title= {Off-line multiple object tracking using candidate selection and the Viterbi algorithm}, 
year= {2005}, volume= {3}, number= {}, pages= {III-109-12}, 
keywords= {maximum likelihood estimation;object detection;particle filtering (numerical methods);Viterbi algorithm;candidate selection;deterministic solution;off-line multiple object tracking;particle filter methods;probabilistic framework;Data mining;Feature extraction;Image sequences;Indexing;Information retrieval;Particle filters;Particle tracking;Performance analysis;Surveillance;Viterbi algorithm},
url={http://www.tara.tcd.ie/bitstream/handle/2262/19821/01530340.pdf},
note={URI: http://hdl.handle.net/2262/19821},
abstract={This paper presents a probabilistic framework for off-line
multiple object tracking. At each timestep, a small set of
deterministic candidates is generated which is guaranteed
to contain the correct solution. Tracking an object within
video then becomes possible using the Viterbi algorithm. In
contrast with particle filter methods where candidates are
numerous and random, the proposed algorithm involves a
few candidates and results in a deterministic solution. Moreover, we consider here off-line applications where past and
future information is exploited. This paper shows that, although basic and very simple, this candidate selection allows the solution of many tracking problems in different
real-world applications and offers a good alternative to particle filter methods for off-line applications.},
doi= {10.1109/ICIP.2005.1530340}, 
ISSN= {1522-4880}, month= {Sept}}

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A.","Kokaram, A.","Dahyot, R."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["F."],"propositions":[],"lastnames":["Pitié"],"suffixes":[]},{"firstnames":["S.","A."],"propositions":[],"lastnames":["Berrani"],"suffixes":[]},{"firstnames":["A."],"propositions":[],"lastnames":["Kokaram"],"suffixes":[]},{"firstnames":["R."],"propositions":[],"lastnames":["Dahyot"],"suffixes":[]}],"booktitle":"IEEE International Conference on Image Processing 2005","title":"Off-line multiple object tracking using candidate selection and the Viterbi algorithm","year":"2005","volume":"3","number":"","pages":"III-109-12","keywords":"maximum likelihood estimation;object detection;particle filtering (numerical methods);Viterbi algorithm;candidate selection;deterministic solution;off-line multiple object tracking;particle filter methods;probabilistic framework;Data mining;Feature extraction;Image sequences;Indexing;Information retrieval;Particle filters;Particle tracking;Performance analysis;Surveillance;Viterbi algorithm","url":"http://www.tara.tcd.ie/bitstream/handle/2262/19821/01530340.pdf","note":"URI: http://hdl.handle.net/2262/19821","abstract":"This paper presents a probabilistic framework for off-line multiple object tracking. 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