A novel and stable human detection and behavior recognition method based on depth sensor

Authors:
Shuqiang Yang;Biao Li
Affiliations:
ATR laboratory at National University of Defense Technology, Changsha, Hunan Province, China;ATR laboratory at National University of Defense Technology, Changsha, Hunan Province, China
Venue:
3D Research
Year:
2013

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Abstract

To improve traditional video surveillance systems' performance on human behavior recognition, a new system has been built. Not visual camera but depth camera is chosen as sensor. To adapt to the most common forward oblique view of camera, a normalized digital elevation map, whose pixel intensity indicates the elevation of the scene, is built from the depth image. Coordinates and intensity in the digital elevation map represent the position information about the scene. Oriented templates are proposed to match and detect the human head robustly in the elevation map. As for the excellent visibility of human head in the elevation map, we track the human head to get trajectory. By combining the trajectory information of human head with the elevation map, several predefined human behaviors are recognized. Our behavior recognition method is straightforward and robust. This uniqueness has no similar with the traditional machine learning and classification framework about human behavior recognition.