Unsupervised Learning of Finite Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Epitomic analysis of appearance and shape
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Person Reidentification Using Spatiotemporal Appearance
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Computer Vision and Image Understanding
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Learning Discriminative Appearance-Based Models Using Partial Least Squares
SIBGRAPI '09 Proceedings of the 2009 XXII Brazilian Symposium on Computer Graphics and Image Processing
Person Re-identification Using Spatial Covariance Regions of Human Body Parts
AVSS '10 Proceedings of the 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance
Detection of loitering individuals in public transportation areas
IEEE Transactions on Intelligent Transportation Systems
Attribute-restricted latent topic model for person re-identification
Pattern Recognition
Person re-identification: what features are important?
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Identity inference: generalizing person re-identification scenarios
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Local distance comparison for multiple-shot people re-identification
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
People reidentification in surveillance and forensics: A survey
ACM Computing Surveys (CSUR)
On-the-fly feature importance mining for person re-identification
Pattern Recognition
Editor's Choice Article: A survey of approaches and trends in person re-identification
Image and Vision Computing
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We propose a novel appearance-based method for person re-identification, that condenses a set of frames of an individual into a highly informative signature, called the Histogram Plus Epitome, HPE. It incorporates complementary global and local statistical descriptions of the human appearance, focusing on the overall chromatic content via histogram representation, and on the presence of recurrent local patches via epitomic analysis. The re-identification performance of HPE is then augmented by applying it as human part descriptor, defining a structured feature called asymmetry-based HPE (AHPE). The matching between (A)HPEs provides optimal performances against low resolution, occlusions, pose and illumination variations, defining state-of-the-art results on all the considered datasets.