AdaBoost with keypoint presence features for real-time vehivle visual detectionReportar como inadecuado




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1 CAOR - Centre de Robotique

Abstract : We present promising results for real-time vehicle visual detection, obtained with adaBoost using new original -keypoints presence features-. These weak-classifiers produce a boolean response based on presence or absence in the tested image of a -keypoint- ~ a SURF interest point with a descriptor sufficiently similar i.e. within a given distance to a reference descriptor characterizing the feature. A first experiment was conducted on a public image dataset containing lateral-viewed cars, yielding 95% recall with 95% precision on test set. Moreover, analysis of the positions of adaBoost-selected keypoints show that they correspond to a specific part of the object category such as -wheel- or -side skirt- and thus have a -semantic- meaning.





Autor: Taoufik Bdiri - Fabien Moutarde - Nicolas Bourdis - Bruno Steux -

Fuente: https://hal.archives-ouvertes.fr/



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