Multi-cue integration for multi-camera tracking

Kuan-Wen Chen*, Yi Ping Hung

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

For target tracking across multiple cameras with disjoint views, previous works usually employed multiple cues and focused on learning a better matching model of each cue, separately. However, none of them had discussed how to integrate these cues to improve performance, to our best knowledge. In this paper, we look into the multi-cue integration problem and propose an unsupervised learning method since a complicated training phase is not always viable. In the experiments, we evaluate several types of score fusion methods and show that our approach learns well and can be applied to large camera networks more easily.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Pages145-148
Number of pages4
DOIs
StatePublished - 18 Nov 2010
Event2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
Duration: 23 Aug 201026 Aug 2010

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Conference

Conference2010 20th International Conference on Pattern Recognition, ICPR 2010
CountryTurkey
CityIstanbul
Period23/08/1026/08/10

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  • Cite this

    Chen, K-W., & Hung, Y. P. (2010). Multi-cue integration for multi-camera tracking. In Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010 (pp. 145-148). [5597619] (Proceedings - International Conference on Pattern Recognition). https://doi.org/10.1109/ICPR.2010.44