ICRA'09 Paper Abstract


Paper FrA11.1

Frintrop, Simone (University of Bonn), Kessel, Markus (University of Bonn)

Most Salient Region Tracking

Scheduled for presentation during the Regular Sessions "Biologically-Inspired Robots - I" (FrA11), Friday, May 15, 2009, 08:30−08:50, Room: 503

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 24, 2022

Keywords Visual Tracking, Computer Vision for Robotics and Automation, Biologically-Inspired Robots


In this paper, we introduce a cognitive approach for object tracking from a mobile platform. The approach is based on a biologically motivated attention system which is able to detect regions of interest in images based on concepts of the human visual system. A top-down guided visual search module of the system enables to especially favor features which fit to a previously learned target object. Here, the appearance of an object is learned online within the first image in which it is detected. In subsequent images, the attention system searches for the target features and builds a top-down, target-related saliency map. This enables to focus on the most relevant features of especially this object in especially this scene without knowing anything about a particular object model or scene in advance. The system is able to operate in real-time and to cope with the requirements of real-world tasks such as illumination variations and other moving objects.



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