  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.
