Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9669561 | Computer Vision and Image Understanding | 2005 | 28 Pages |
Abstract
In this paper, we present a new bimodal attention system for robotic applications capable of processing data from different sensor modes simultaneously. Considering several sensor modalities is an obvious approach to regard a variety of object properties. Nevertheless, conventional attention systems only regard the processing of camera images. In contrast to these systems, the input data to our system are provided by a bimodal 3D laser scanner, mounted on top of an autonomous mobile robot. In a single 3D scan pass, the scanner yields range as well as reflectance data. Both data modes are illumination independent, yielding a robust approach that enables all day operation. Data from both laser modes are fed into our attention system built on principles of one of the standard models of visual attention by Koch and Ullman. The system computes conspicuities of both modes in parallel and fuses them into one saliency map. The focus of attention is directed to the most salient points in this map sequentially. We present results on recorded scans of indoor and outdoor scenes showing the respective advantages of the sensor modalities enabling the mode-specific detection of different object properties. Furthermore, we show as an application of the attention system the recognition of objects for building semantic 3D maps of the robot's environment.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Simone Frintrop, Erich Rome, Andreas Nüchter, Hartmut Surmann,