Multi-cue integration for multi-camera tracking
Journal
Proceedings - International Conference on Pattern Recognition
Pages
145-148
Date Issued
2010
Author(s)
Chen, K.-W.
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. © 2010 IEEE.
Other Subjects
Camera network; Cue integration; Disjoint views; Matching models; Multi-camera tracking; Multiple cameras; Score fusion; Training phase; Unsupervised learning method; Pattern recognition; Target tracking; Unsupervised learning; Video cameras; Cameras
Type
conference paper