Performance evaluation of local features in human classification and detection
Detecting pedestrians accurately is the first fundamental step for many computer vision applications such as video surveillance, smart vehicles, intersection traffic analysis and so on. The authors present an experimental study on pedestrian detection using state-of-the-art local feature extraction and support vector machine (SVM) classifiers. The performance of pedestrian detection using region covariance, histogram of oriented gradients (HOG) and local receptive fields (LRF) feature...[Show more]
|Collections||ANU Research Publications|
|Source:||IET Computer Vision|
|01_Paisitkriangkrai_Performance_evaluation_of_2008.pdf||1.18 MB||Adobe PDF||Request a copy|
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