mit artificial intelligence laboratory — research directions visual detection systems tomaso...
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MIT Artificial Intelligence Laboratory — Research Directions
Visual Detection SystemsTomaso 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
. . .
. . .
newnew imageimage
PedestrianPedestrian
Non-Non-pedestrianpedestrian
Trainable Trainable SystemSystem
……....
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 Database1000+ Real, 3000+ VIRTUAL50,0000+ 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
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MIT Artificial Intelligence Laboratory — Research Directions
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MIT Artificial Intelligence Laboratory — Research Directions
Results
The system is capable of detecting people whenthey are running or walking. It is also able to detectpeople when all their body parts are not detectable orwhen they are slightly rotated in depth.
MIT Artificial Intelligence Laboratory — Research Directions
Results
The system is capable of detecting partially occluded people.
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