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Optimal Detection and Tracking of Feature Points using Mutual Information

A. Dame 1 Eric Marchand 1 
1 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : This paper proposes a new way to achieve feature point tracking using the entropy of the image. Sum of Squared Differences (SSD) is widely considered in differential trackers such as the KLT. Here, we consider another metric called Mutual Information (MI), which is far less sensitive to changes in the lighting condition and to a wide class of non-linear image transformation. Since mutual-information is used as an energy function to be maximized to track each points, a new feature selection, which is optimal for this metric, is proposed. Results under various complex conditions are presented. Comparison with the classical KLT tracker are proposed.
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Submitted on : Friday, November 27, 2009 - 4:42:53 PM
Last modification on : Thursday, January 20, 2022 - 4:20:27 PM
Long-term archiving on: : Thursday, June 30, 2011 - 11:59:14 AM


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  • HAL Id : inria-00436742, version 1


A. Dame, Eric Marchand. Optimal Detection and Tracking of Feature Points using Mutual Information. IEEE Int. Conf. on Image Processing, ICIP'09, 2009, Cairo, Egypt, Egypt. ⟨inria-00436742⟩



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