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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. © 2005 IEEE.

Original publication

DOI

10.1109/ROBOT.2005.1570107

Type

Journal article

Journal

Proceedings - IEEE International Conference on Robotics and Automation

Publication Date

01/12/2005

Volume

2005

Pages

125 - 130