Robust tracking with weighted online structured learning
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Local log-euclidean covariance matrix (L2ECM) for image representation and its applications
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Online spatio-temporal structural context learning for visual tracking
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Dynamic objectness for adaptive tracking
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Structured visual tracking with dynamic graph
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Multitarget tracking of pedestrians in video sequences based on particle filters
Advances in Multimedia
A survey of appearance models in visual object tracking
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
A vector quantization approach for image segmentation based on SOM neural network
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Visual tracking using superpixel-based appearance model
ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
Integrating tracking with fine object segmentation
Image and Vision Computing
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
A novel particle filter with implicit dynamic model for irregular motion tracking
Machine Vision and Applications
Visual tracking via weakly supervised learning from multiple imperfect oracles
Pattern Recognition
Object tracking using learned feature manifolds
Computer Vision and Image Understanding
Abrupt motion tracking using a visual saliency embedded particle filter
Pattern Recognition
Collaborative object tracking model with local sparse representation
Journal of Visual Communication and Image Representation
Multi-Target Tracking by Online Learning a CRF Model of Appearance and Motion Patterns
International Journal of Computer Vision
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While numerous algorithms have been proposed for object tracking with demonstrated success, it remains a challenging problem for a tracker to handle large change in scale, motion, shape deformation with occlusion. One of the main reasons is the lack of effective image representation to account for appearance variation. Most trackers use high-level appearance structure or low-level cues for representing and matching target objects. In this paper, we propose a tracking method from the perspective of mid-level vision with structural information captured in superpixels. We present a discriminative appearance model based on superpixels, thereby facilitating a tracker to distinguish the target and the background with mid-level cues. The tracking task is then formulated by computing a target-background confidence map, and obtaining the best candidate by maximum a posterior estimate. Experimental results demonstrate that our tracker is able to handle heavy occlusion and recover from drifts. In conjunction with online update, the proposed algorithm is shown to perform favorably against existing methods for object tracking.