Pedestrian Orientation Estimation
PATTERN RECOGNITION, GCPR 2014(2014)
摘要
This paper addresses the task of estimating the orientation of pedestrians from monocular images provided by an automotive camera. From an initial detection of a pedestrian, we analyze the area within their bounding box and give an estimation of the orientation. Using ground truth mocap data, we define the orientations as a direction and a rough human pose. A random forest classifier trained on this data using HOG features assigns each detected pedestrian to their orientation cluster. Evaluation of the method is performed on a new dataset and on a publicly available dataset showing improved results.
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关键词
Ground Truth, Random Forest, Leaf Node, Training Image, Holistic Approach
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