Feature Matching using Co-inertia Analysis for People Tracking

Abstract : Robust object tracking is a challenging computer vision problem due to dynamic changes in object pose, illumination, appearance and occlusions. Tracking objects between frames requires accurate matching of their features. We investigate real time matching of mobile object features for frame to frame tracking. This paper presents a new feature matching approach between objects for tracking that incorporates one of the multivariate analysis method called Co-Inertia Analysis abbreviated as COIA. This approach is being introduced to compute the similarity between Histogram of Oriented Gradients (HOG) features of the tracked objects. Experiments conducted shows the effectiveness of this approach for mobile object feature tracking.
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Communication dans un congrès
The 9th International Conference on Computer Vision Theory and Applications (VISAPP 2014), Jan 2014, Lisbon, Portugal. 2014
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https://hal.inria.fr/hal-00909566
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Srinidhi Mukanahallipatna Simha, Duc Phu Chau, François Bremond. Feature Matching using Co-inertia Analysis for People Tracking. The 9th International Conference on Computer Vision Theory and Applications (VISAPP 2014), Jan 2014, Lisbon, Portugal. 2014. 〈hal-00909566〉

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