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Robust Object Detection at Regions of Interest with an Application in Ball Recognition

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5 Author(s)
Mitri, S. ; Fraunhofer Institute for Autonomous Intelligent Systems (AIS) Schloss Birlinghoven, D-53754 Sankt Augustin, Germany ; Frintrop, S. ; Pervolz, K. ; Surmann, H.
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In this paper, we present a new combination of a biologically inspired attention system (VOCUS – Visual Object detection with a CompUtational attention System) with a robust object detection method. As an application, we built a reliable system for ball recognition in the RoboCup context. Firstly, VOCUS finds regions of interest generating a hypothesis for possible locations of the ball. Secondly, a fast classifier verifies the hypothesis by detecting balls at regions of interest. The combination of both approaches makes the system highly robust and eliminates false detections. Furthermore, the system is quickly adaptable to balls in different scenarios: The complex classifier is universally applicable to balls in every context and the attention system improves the performance by learning scenario-specific features quickly from only a few training examples.

Published in:

Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on

Date of Conference:

18-22 April 2005