3 June 2014 Occluded human recognition for a leader following system using 3D range and image data in forest environment
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Abstract
This paper describes the occluded target recognition and tracking method for a leader-following system by fusing 3D range and image data acquired from 3D light detection and ranging (LIDAR) and a color camera installed on an autonomous vehicle in forest environment. During 3D data processing, the distance-based clustering method has an instinctive problem in close encounters. In the tracking phase, we divide an object tracking process into three phases based on occlusion scenario; before an occlusion (BO) phase, a partially or fully occlusion phase and after an occlusion (AO) phase. To improve the data association performance, we use camera's rich information to find correspondence among objects during above mentioned three phases of occlusion. In this paper, we solve a correspondence problem using the color features of human objects with the sum of squared distance (SSD) and the normalized cross correlation (NCC). The features are integrated with derived windows from Harris corner. The experimental results for a leader following on an autonomous vehicle are shown with LIDAR and camera for improving a data association problem in a multiple object tracking system.
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Kuk Cho, Muhammad Ilyas, Seung-Ho Baeg, Sangdeok Park, "Occluded human recognition for a leader following system using 3D range and image data in forest environment", Proc. SPIE 9084, Unmanned Systems Technology XVI, 90840W (3 June 2014); doi: 10.1117/12.2053209; https://doi.org/10.1117/12.2053209
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