Object Detection using the Kinect

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.