Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-Line Selection of Discriminative Tracking Features
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Robust Tracking Using Foreground-Background Texture Discrimination
International Journal of Computer Vision
A Closed Form Solution to Natural Image Matting
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
IEEE Transactions on Pattern Analysis and Machine Intelligence
A tutorial on spectral clustering
Statistics and Computing
Incremental Learning for Robust Visual Tracking
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Robust online appearance models for visual tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Object Tracking Based on an Effective Appearance Filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sequential Karhunen-Loeve basis extraction and its application to images
IEEE Transactions on Image Processing
Visual tracking and recognition using appearance-adaptive models in particle filters
IEEE Transactions on Image Processing
Relevance feedback strategies for artistic image collections tagging
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Feature space warping relevance feedback with transductive learning
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Robust visual tracking with structured sparse representation appearance model
Pattern Recognition
Robust visual tracking with discriminative sparse learning
Pattern Recognition
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
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In object tracking problem, most methods assume brightness constancy or subspace constancy, which are violated in practice. In this paper, the object tracking problem is considered as a transductive learning problem and a robust tracking method is proposed under intrinsic and extrinsic varieties. The object not only fits the object model, but also has the same cluster with the previous objects, which are the labeled data. By constraining the global and local information, the cost function is constructed firstly. The solution for minimizing the cost function can be solved by a simple linear algebra with graph Laplacian. Moreover, a novel graph is constructed over the positive samples and candidate patches, which can simultaneously learn the object's global appearance model and the local intrinsic geometric structure of all the patches. Furthermore, a heuristic positive samples selection scheme is adopted to make the method more effective. The proposed method is tested on different videos, which undergo large pose, expression, illumination and partial occlusion, and compared with state-of-the-art algorithms. Experimental results and comparative studies are provided to demonstrate the efficiency of the proposed method.