Context-free attentional operators: the generalized symmetry transform
International Journal of Computer Vision - Special issue on qualitative vision
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Visual Learning for Object Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
Resolving Motion Correspondence for Densely Moving Points
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Learning of Finite Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation
International Journal of Computer Vision
Color-Based Probabilistic Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color-Based Tracking of Heads and Other Mobile Objects at Video Frame Rates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Interpreting Face Images Using Active Appearance Models
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Epitomic analysis of appearance and shape
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
Probabilistic Object Tracking Using Multiple Features
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluating Multi-Object Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Covariance Tracking using Model Update Based on Lie Algebra
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
3D People Tracking with Gaussian Process Dynamical Models
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Person Reidentification Using Spatiotemporal Appearance
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Approximate Bayesian Multibody Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
Computer Vision and Image Understanding
Pedestrian Detection via Classification on Riemannian Manifolds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Learning Pairwise Dissimilarity Profiles for Appearance Recognition in Visual Surveillance
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Symmetry, Perspectivity, and Level-Set-Based Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Discriminative Appearance-Based Models Using Partial Least Squares
SIBGRAPI '09 Proceedings of the 2009 XXII Brazilian Symposium on Computer Graphics and Image Processing
Online subjective feature selection for occlusion management in tracking applications
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Bridging the gaps between cameras
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Person Re-identification Using Haar-based and DCD-based Signature
AVSS '10 Proceedings of the 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance
Multiple-Shot Person Re-identification by HPE Signature
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Multiple-shot human re-identification by Mean Riemannian Covariance Grid
AVSS '11 Proceedings of the 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance
Detection of loitering individuals in public transportation areas
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Editor's Choice Article: A survey of approaches and trends in person re-identification
Image and Vision Computing
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This work proposes a method to characterize the appearance of individuals exploiting body visual cues. The method is based on a symmetry-driven appearance-based descriptor and a matching policy that allows to recognize an individual. The descriptor encodes three complementary visual characteristics of the human appearance: the overall chromatic content, the spatial arrangement of colors into stable regions, and the presence of recurrent local motifs with high entropy. The characteristics are extracted by following symmetry and asymmetry perceptual principles, that allow to segregate meaningful body parts and to focus on the human body only, pruning out the background clutter. The descriptor exploits the case where we have a single image of the individual, as so as the eventuality that multiple pictures of the same identity are available, as in a tracking scenario. The descriptor is dubbed Symmetry-Driven Accumulation of Local Features (SDALFs). Our approach is applied to two different scenarios: re-identification and multi-target tracking. In the former, we show the capabilities of SDALF in encoding peculiar aspects of an individual, focusing on its robustness properties across dramatic low resolution images, in presence of occlusions and pose changes, and variations of viewpoints and scene illumination. SDALF has been tested on various benchmark datasets, obtaining in general convincing performances, and setting the state of the art in some cases. The latter scenario shows the benefits of using SDALF as observation model for different trackers, boosting their performances under different respects on the CAVIAR dataset.