A Mixed-State Condensation Tracker with Automatic Model-Switching
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Using Particles to Track Varying Numbers of Interacting People
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Appearance Modeling for Tracking in Multiple Non-Overlapping Cameras
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
ACM Computing Surveys (CSUR)
EURASIP Journal on Applied Signal Processing
Non-overlapping Distributed Tracking System Utilizing Particle Filter
Journal of VLSI Signal Processing Systems
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Bridging the gaps between cameras
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
| Hi-index | 0.00 |
This article presents a novel approach to person tracking within large-scale indoor environments monitored by non-overlapping field-of-view camera networks.We address the image-based tracking problem with distributed particle filters using a hierarchical color model. The novelty of our approach resides in the embedding of an already-seenpeople database in the particle filter framework. Doing so, the filter performs not only position estimation but also does establish identity probabilities for the current targets in the network. Thus we use online person re-identification as a way to introduce continuity to track people in disjoint camera networks. No calibration stage is required. We demonstrate the performances of our approach on a 5 camera-disjoint network and a 16-person database.