DTIC ADA586027: Implementation of a Cascaded Histogram pdf

DTIC ADA586027: Implementation of a Cascaded Histogram

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In this report, we present our implementation of a cascaded Histogram of Oriented Gradient (HOG) based pedestrian detector. Most human detection algorithms can be implemented as a cascade of classifiers to decrease computation time while maintaining approximately the same performance. Although cascaded versions of Dalal and Triggs s HOG detector already exist, we aim to provide a more detailed explanation of an implementation than is currently available. We also use Asymmetric Boosting instead of Adaboost to train the cascade stages. We show that this approach reduces the number of weak classifiers needed per stage. We present the results of our detector on the INRIA pedestrian detection dataset and compare them to the results provided by Dalal and Triggs

• Creator/s: Defense Technical Information Center
• Date: 9/1/2013
• Year: 2013
• Book Topics/Themes: DTIC Archive, , ARMY RESEARCH LAB ADELPHI MD SENSORS AND ELECTRON DEVICES DIRECTORATE, *DETECTION, *WALKING, ALGORITHMS, GRADIENTS, PERFORMANCE(HUMAN), SURVEILLANCE

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