MIT Artificial Intelligence Laboratory — Research Directions Visual Detection Systems Tomaso Poggio
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
MIT Artificial Intelligence Laboratory — Research Directions More on the Object Classification System... new image Pedestrian Non- pedestrian Trainable System …..
MIT Artificial Intelligence Laboratory — Research Directions Learning Object Detection: Car Detection - Training
MIT Artificial Intelligence Laboratory — Research Directions Learning Object Detection: Car Detection - Results
MIT Artificial Intelligence Laboratory — Research Directions Trainable System for Object Detection: Face Detection - Results Training Database Real, VIRTUAL 50,0000+ Non-Face Pattern Sung, Poggio 1995
MIT Artificial Intelligence Laboratory — Research Directions Trainable System for Object Detection: Eye Detection - Results
MIT Artificial Intelligence Laboratory — Research Directions Trainable System for Object Detection: Pedestrian Detection - Training
MIT Artificial Intelligence Laboratory — Research Directions Trainable System for Object Detection: Pedestrian Detection - Results
MIT Artificial Intelligence Laboratory — Research Directions System Installed in Experimental Mercedes A fast version, integrated with a real-time obstacle detection system MPEG
MIT Artificial Intelligence Laboratory — Research Directions
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.
MIT Artificial Intelligence Laboratory — Research Directions Results The system is capable of detecting partially occluded people.