Pedestrian detection occupies a vital status in the field of computer vision because of its important applications such as intelligent surveillance system, intelligent transport system, robotics and automotive safety. To improve the algorithm performance for pedestrian detection, and especially to cope with the partial occlusion problem, a novel pedestrian detection framework is presented based on the improved adaptive boosting (Adaboost) algorithm and enhanced cascade detector output. There are three major contributions. First, aiming to solve the drawbacks of the conventional Adaboost method, a modified Adaboost algorithm is proposed for more accurate detecting pedestrian. Second, a simple yet effective way is proposed, called local area marking map (LAMM), to decide whether the partial occlusion occurs in a detection window. At last, in order to handle the partial occlusion problem, an enhanced cascade scheme is derived from the LAMM information. Additionally, the histograms of oriented gradients features are combined with the proposed framework. The authors validate the significant improvements of the proposed method by extensive experiments testing on Institut National de Recherche en Informatique et en Automatique (INRIA), Daimler, by performance evaluation of tracking and by surveillance 2001 (PETS'2001) datasets with comparisons to several state-of-the-art methods.
Detection of partially occluded pedestrians by an enhanced cascade detector
IET Intelligent Transport Systems ; 8 , 7 ; 621-630
2014-11-01
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
object detection , robotics , intelligent transport system , computer vision , Adaboost method , histograms of oriented gradients , learning (artificial intelligence) , pedestrians , Adaboost algorithm , cascade detector enhancement , intelligent surveillance system , LAMM , traffic engineering computing , adaptive boosting algorithm , local area marking map , partially occluded pedestrian detection , automotive safety
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Detection of partially occluded pedestrians by an enhanced cascade detector
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