The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
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
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Affine Object Tracking with Kernel-Based Spatial-Color Representation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Multiple Collaborative Kernel Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
On-Line Density-Based Appearance Modeling for Object Tracking
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Efficient Optimal Kernel Placement for Reliable Visual Tracking
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Intelligent Collaborative Tracking by Mining Auxiliary Objects
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
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
Kernel-based Template Alignment
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Measurement integration under inconsistency for robust tracking
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Homography-based 2D Visual Tracking and Servoing
International Journal of Robotics Research
A Rao-Blackwellized particle filter for EigenTracking
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Nonparametri information fusion for motion estimation
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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In object tracking, visual features may not be discriminative enough to estimate high dimensional motion parameters accurately, and complex motion estimation is computationally expensive due to a large search space. To tackle these problems, a reasonable strategy is to track small components within the target independently in lower dimensional motion parameter spaces (e.g., translation only) and then estimate the overall high dimensional motion (e.g., translation, scale and rotation) by statistically integrating the individual tracking results. Although tracking each component in a lower dimensional space is more reliable and faster, it is not trivial to combine the local motion information and estimate global parameters in a robust way because the individual component motions are frequently inconsistent. We propose a robust fusion algorithm to estimate the complex motion parameters using variable-bandwidth mean-shift. By employing correlation-based uncertainty modeling and fusion of individual components, the motion parameter that is robust to outliers can be detected with variable-bandwidth density-based fusion (VBDF) algorithm. In addition, we describe a method to update target appearance model for each component adaptively based on the component motion consistency. We present various tracking results and compare the performance of our algorithm with others using real video sequences.