A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Information-theoretic metric learning
Proceedings of the 24th international conference on Machine learning
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
Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding
International Journal of Computer Vision
Multiple-Shot Person Re-identification by HPE Signature
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Bag of soft biometrics for person identification
Multimedia Tools and Applications
Describable Visual Attributes for Face Verification and Image Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image ranking and retrieval based on multi-attribute queries
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Quantifying and Transferring Contextual Information in Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Attribute learning for understanding unstructured social activity
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Learning articulated body models for people re-identification
Proceedings of the 21st ACM international conference on Multimedia
Domain transfer for person re-identification
Proceedings of the 4th ACM/IEEE international workshop on Analysis and retrieval of tracked events and motion in imagery stream
People reidentification in surveillance and forensics: A survey
ACM Computing Surveys (CSUR)
Editor's Choice Article: A survey of approaches and trends in person re-identification
Image and Vision Computing
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Visual identification of an individual in a crowded environment observed by a distributed camera network is critical to a variety of tasks including commercial space management, border control, and crime prevention. Automatic re-identification of a human from public space CCTV video is challenging due to spatiotemporal visual feature variations and strong visual similarity in people's appearance, compounded by low-resolution and poor quality video data. Relying on re-identification using a probe image is limiting, as a linguistic description of an individual's profile may often be the only available cues. In this work, we show how mid-level semantic attributes can be used synergistically with low-level features for both identification and re-identification. Specifically, we learn an attribute-centric representation to describe people, and a metric for comparing attribute profiles to disambiguate individuals. This differs from existing approaches to re-identification which rely purely on bottom-up statistics of low-level features: it allows improved robustness to view and lighting; and can be used for identification as well as re-identification. Experiments demonstrate the flexibility and effectiveness of our approach compared to existing feature representations when applied to benchmark datasets.