Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
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
Principal Axis-Based Correspondence between Multiple Cameras for People Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Person Reidentification Using Spatiotemporal Appearance
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Tracking people across disjoint camera views by an illumination-tolerant appearance representation
Machine Vision and Applications
Computer Vision and Image Understanding
Bayesian-Competitive Consistent Labeling for People Surveillance
IEEE Transactions on Pattern Analysis and Machine Intelligence
HECOL: Homography and epipolar-based consistent labeling for outdoor park surveillance
Computer Vision and Image Understanding
Object matching in disjoint cameras using a color transfer approach
Machine Vision and Applications
Object handoff between uncalibrated views without planar ground assumption
Pattern Recognition Letters
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Correspondence-Free Activity Analysis and Scene Modeling in Multiple Camera Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
Particle filtering with multiple and heterogeneous cameras
Pattern Recognition
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
Sequential Monte Carlo methods for multiple target tracking anddata fusion
IEEE Transactions on Signal Processing
Consistent labeling of tracked objects in multiple cameras with overlapping fields of view
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-splitting competitive learning: a new on-line clustering paradigm
IEEE Transactions on Neural Networks
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Tracking people across multiple cameras with non-overlapping views is a challenging task, since their observations are separated in time and space and their appearances may vary significantly. This paper proposes a Bayesian model to solve the consistent labeling problem across multiple non-overlapping camera views. Significantly different from related approaches, our model assumes neither people are well segmented nor their trajectories across camera views are estimated. We formulate a spatial-temporal probabilistic model in the hypothesis space that consists the potentially matched objects between the exit field of view (FOV) of one camera and the entry FOV of another camera. A competitive major color spectrum histogram representation (CMCSHR) for appearance matching between two objects is also proposed. The proposed spatial-temporal and appearance models are unified by a maximum-a-posteriori (MAP) Bayesian model. Based on this Bayesian model, when a detected new object corresponds to a group hypothesis (more than one object), we further develop an online method for online correspondence update using optimal graph matching (OGM) algorithm. Experimental results on three different real scenarios validate the proposed Bayesian model approach and the CMCSHR method. The results also show that the proposed approach is able to address the occlusion problem/group problem, i.e. finding the corresponding individuals in another camera view for a group of people who walk together into the entry FOV of a camera.