1. MIT Artificial Intelligence Laboratory — Research Directions Visual Detection Systems Tomaso Poggio

2. MIT Artificial Intelligence Laboratory — Research Directions Developing a general paradigm for object detection in cluttered scenes Applications: target detection, visual data base search... Trainable system…for “any” desired object class The Problem Object Categorization/Detection

3. MIT Artificial Intelligence Laboratory — Research Directions More on the Object Classification System... new image Pedestrian Non- pedestrian Trainable System …..

4. MIT Artificial Intelligence Laboratory — Research Directions Learning Object Detection: Car Detection - Training

5. MIT Artificial Intelligence Laboratory — Research Directions Learning Object Detection: Car Detection - Results

6. MIT Artificial Intelligence Laboratory — Research Directions Trainable System for Object Detection: Face Detection - Results Training Database 1000+ Real, 3000+ VIRTUAL 50,0000+ Non-Face Pattern Sung, Poggio 1995

7. MIT Artificial Intelligence Laboratory — Research Directions Trainable System for Object Detection: Eye Detection - Results

8. MIT Artificial Intelligence Laboratory — Research Directions Trainable System for Object Detection: Pedestrian Detection - Training

9. MIT Artificial Intelligence Laboratory — Research Directions Trainable System for Object Detection: Pedestrian Detection - Results

10. MIT Artificial Intelligence Laboratory — Research Directions System Installed in Experimental Mercedes A fast version, integrated with a real-time obstacle detection system MPEG

11. MIT Artificial Intelligence Laboratory — Research Directions

12. Results The system is capable of detecting people when they are running or walking. It is also able to detect people when all their body parts are not detectable or when they are slightly rotated in depth.

13. MIT Artificial Intelligence Laboratory — Research Directions Results The system is capable of detecting partially occluded people.