Tracking Across Multiple Cameras With Disjoint Views
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Diffusion Distance for Histogram Comparison
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Pattern Recognition Letters
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Sequences Association for People Re-identification across Multiple Non-overlapping Cameras
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
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In this paper we address the problem of re-identification of people: given a camera network with non-overlapping fields of view, we study the problem of how to correctly pair detections in different cameras (one to many problem, search for similar cases) ormatch detections to a database of individuals (one to one, search for best match case). We propose a novel color histogram based features which increases the re-identification rate. Furthermore we evaluate five different classifiers: three fixed distance metrics, one learned distance metric and a classifier based on sparse representation, novel to the field of re-identification. A new database alongside with the matlab code produced are made available on request.