1. Human Detection using depth
Zach Robertson

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

3. Problems Alignment of RGB and Depth Images Segmentation
Human Detection

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

5. 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

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

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

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

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