Introducing New AdaBoost Features for Real-Time Vehicle Detection

Details Introducing New AdaBoost Features for Real-Time Vehicle Detection Introducing New AdaBoost Features for Real-Time Vehicle Detection

2009-10-07

arxiv.org/abs/0910.1293v1

COGIS'07 conference on COGnitive systems with Interactive Sensors, Stanford, Palo Alto : United States (2007)

Computer Science

Computer Vision and Pattern Recognition

Scientific paper

This paper shows how to improve the real-time object detection in complex robotics applications, by exploring new visual features as AdaBoost weak classifiers. These new features are symmetric Haar filters (enforcing global horizontal and vertical symmetry) and N-connexity control points. Experimental evaluation on a car database show that the latter appear to provide the best results for the vehicle-detection problem.

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