EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Elliptical Head Tracking Using Intensity Gradients and Color Histograms
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
Integral Histogram: A Fast Way To Extract Histograms in Cartesian Spaces
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Robust Fragments-based Tracking using the Integral Histogram
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Incremental Learning for Robust Visual Tracking
International Journal of Computer Vision
Semi-supervised On-Line Boosting for Robust Tracking
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Object tracking using SIFT features and mean shift
Computer Vision and Image Understanding
Computer Vision and Image Understanding
Robust Multiperson Tracking from a Mobile Platform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond pixels: exploring new representations and applications for motion analysis
Beyond pixels: exploring new representations and applications for motion analysis
Human tracking using convolutional neural networks
IEEE Transactions on Neural Networks
3D head tracking based on recognition and interpolation using a time-of-flight depth sensor
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Adaptive multi-cue tracking by online appearance learning
Neurocomputing
Robust Object Tracking with Online Multiple Instance Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new framework for on-line object tracking based on SURF
Pattern Recognition Letters
Recent advances and trends in visual tracking: A review
Neurocomputing
Robust Visual Tracking and Vehicle Classification via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking objects using shape context matching
Neurocomputing
Monocular tracking of 3d human motion with a coordinated mixture of factor analyzers
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
IEEE Transactions on Pattern Analysis and Machine Intelligence
Microsoft Kinect Sensor and Its Effect
IEEE MultiMedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual tracking via adaptive structural local sparse appearance model
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Multi-spectral saliency detection
Pattern Recognition Letters
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Visual tracking is a central topic in computer vision. However, the accurate localization of target object in extreme conditions (such as occlusion, scaling, illumination change, and shape transformation) still remains a challenge. In this paper, we explore utilizing multi-cue information to ensure a robust tracking. Optical flow, color and depth clues are simultaneously incorporated in our framework. The optical flow can get a rough estimation of the target location. Then the part-based structure is adopted to establish the precise position, combining both color and depth statistics. In order to validate the robustness of the proposed method, we take four video sequences of different demanding situations and compare our method with five competitive ones representing state of the arts. Experiments prove the effectiveness of the proposed method.