A robust and scalable approach to face identification
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Person re-identification by descriptive and discriminative classification
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Person re-identification using appearance classification
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part II
Person re-identification based on global color context
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
Multiple-shot person re-identification by chromatic and epitomic analyses
Pattern Recognition Letters
Boosted human re-identification using Riemannian manifolds
Image and Vision Computing
Part-based spatio-temporal model for multi-person re-identification
Pattern Recognition Letters
Intelligent multi-camera video surveillance: A review
Pattern Recognition Letters
Sparse coding and dictionary learning for symmetric positive definite matrices: a kernel approach
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Set based discriminative ranking for recognition
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Learning to match appearances by correlations in a covariance metric space
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Relaxed pairwise learned metric for person re-identification
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Person re-identification: what features are important?
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Towards person identification and re-identification with attributes
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Local descriptors encoded by fisher vectors for person re-identification
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
Symmetry-driven accumulation of local features for human characterization and re-identification
Computer Vision and Image Understanding
A comparative study of several feature extraction methods for person re-identification
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Human reidentification with transferred metric learning
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Covariance descriptor multiple object tracking and re-identification with colorspace evaluation
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
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)
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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Appearance information is essential for applications such as tracking and people recognition. One of the main problems of using appearance-based discriminative models is the ambiguities among classes when the number of persons being considered increases. To reduce the amount of ambiguity, we propose the use of a rich set of feature descriptors based on color, textures and edges. Another issue regarding appearance modeling is the limited number of training samples available for each appearance. The discriminative models are created using a powerful statistical tool called Partial Least Squares (PLS), responsible for weighting the features according to their discriminative power for each different appearance. The experimental results, based on appearance-based person recognition, demonstrate that the use of an enriched feature set analyzed by PLS reduces the ambiguity among different appearances and provides higher recognition rates when compared to other machine learning techniques.