Object Detection using the Kinect

Report No. ARL-TN-0474
Authors: Jason Owens
Date/Pages: March 2012; 24 pages
Abstract: We investigate an object detection system that uses both image and three-dimensional (3-D) point cloud data captured from the low-cost Microsoft Kinect vision sensor. The system works in three parts: image and point cloud data are fed into two components; the point cloud is segmented into hypothesized objects and the image region for those objects are extracted; and finally, a histogram of oriented gradient (HOG) descriptors are used for detection using a sliding window scheme. We evaluate this system by detecting backpacks on a challenging set of capture sequences in an indoor office environment with encouraging results.
Distribution: Approved for public release
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Last Update / Reviewed: March 1, 2012