Robust regression methods for computer vision: a review
International Journal of Computer Vision
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
ASSET-2: Real-Time Motion Segmentation and Shape Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
A Real-time Computer Vision System for Measuring Traffic Parameters
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Real Time Face and Object Tracking as a Component of a Perceptual User Interface
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Object Recognition with Informative Features and Linear Classification
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
Point Matching under Large Image Deformations and Illumination Changes
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Mean-Shift Tracking via a New Similarity Measure
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
Spatiograms versus Histograms for Region-Based Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
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
Object Tracking using Color Correlogram
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
A Contour-Based Moving Object Detection and Tracking
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
Robust template tracking with drift correction
Pattern Recognition Letters
Probabilistic tracking in joint feature-spatial spaces
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Automated vision tracking of project related entities
Advanced Engineering Informatics
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We present a novel histogram-based tracking algorithm, which is a generalization of the template matching Lucas-Kanade algorithm (and in particular of the inverse compositional version which is more efficient). The algorithm does not make use of any spatial kernel. Instead, the dependency of the histogram on the warping parameters is introduced via a feature kernel. This fact helps us to overcome several limitations of kernel-based methods. The target is represented by a collection of patch-based histograms, thus retaining spatial information. A robust statistics scheme assigns weights to the different patches, rendering the algorithm robust to partial occlusions and appearance changes. We present the algorithm for 1-D histograms (e.g. gray-scale), however extending the algorithm to handle higher dimensional histograms (e.g. color) is straightforward. Our method applies to any warping transformation that forms a group, and to any smooth feature. It has the same asymptotic complexity as the original inverse compositional template matching algorithm. We present experimental results which demonstrate the robustness of our algorithm, using only gray-scale histograms.