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Visual Detection Systems Tomaso Poggio MIT Artificial Intelligence Laboratory — Research Directions Object Categorization/Detection The Problem • Developing a general paradigm for object detection in cluttered scenes • Applications: target detection, visual data base search... • Trainable system…for “any” desired object class MIT Artificial Intelligence Laboratory — Research Directions More on the Object Classification System ... ... Pedestrian new image Trainable System ….. Nonpedestrian 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 1000+ Real, 3000+ 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 QuickTime™ and a decompressor are needed to see this picture. A fast version, integrated with a real-time obstacle detection system MPEG MIT Artificial Intelligence Laboratory — Research Directions QuickTime™ and a decompressor are needed to see this picture. 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. MIT Artificial Intelligence Laboratory — Research Directions
