Pay Attention When Selecting Features
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Abstract
In this paper, we propose a new, hierarchical approach to landmark selection for simultaneous robot localization and
mapping based on visual sensors: a biologically motivated
attention system finds salient regions of interest (ROIs) in
images, and within these regions, Harris corners are detected.
This combines the advantages of the ROIs (reducing
complexity, enabling good redetactability of regions) with
the advantages of the Harris corners (high stability). Reducing
complexity is important to meet real-time requirements
and stability of features is essential to compute the
depth of landmarks from structure from motion with a small
baseline. We show that the number of landmarks is highly
reduced compared to all Harris corners while maintaining
the stability of features for the mapping task.
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2006-08
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