Signal Processing for Computer Vision
Signal Processing for Computer Vision
Feature Kernel Functions: Improving SVMs Using High-Level Knowledge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Evaluation of subpixel tracking algorithms
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
IEEE Transactions on Image Processing
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The estimation of a patch position in an image is a long established but still relevant topic with many applications, e.g. pose estimation and tracking in image sequences. In most systems the position estimate needs to be fused with other estimates, and hence, covariance information is required to weight the different estimates in the right way. In this paper we address the issue with covariance estimation in the case of sum of absolute difference (SAD) block matching. First, we derive the theory for covariance estimation in the case of SAD matching. Second, we evaluate the suggested method in a virtual 3D patch tracking scenario in order to verify the performance in real-world scenarios.