Human Detection using depth Zach Robertson

Papers Read Object Detection with Discriminatively Trained Part-Based Models A little on HOG Mean Shift

Problems Alignment of RGB and Depth Images Segmentation Human Detection

Initial Tests Removing background using masks based on the depth data Dilating the masks Applying Petro’s algorithm on the result

Further Tests Using Edison code to segment depth data then apply mask At each depth level Petro’s algorithm was applied Allowed for the threshold to be increased significantly, from -0.3 to -1.1

Petro’s Algorithm with no depth, low and high threshold

Third Test Align depth and RGB images then apply Petro’s algorithms

Petro’s Algorithm with no depth, low and high threshold

Future Work Apply head and shoulder detector Apply head detector Training Petro’s algorithms with depth images