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Saliency-Guided Perceptual Grouping Using Motion Cues in Region-Based Artificial Visual Attention

J. Tünnermann,Dieter Enns,B. Mertsching

Published 2013 in arXiv.org

ABSTRACT

Region-based artificial attention constitutes a framework for bio-inspired attentional processes on an intermediate abstraction level for the use in computer vision and mobile robotics. Segmentation algorithms produce regions of coherently colored pixels. These serve as proto-objects on which the attentional processes determine image portions of relevance. A single region---which not necessarily represents a full object---constitutes the focus of attention. For many post-attentional tasks, however, such as identifying or tracking objects, single segments are not sufficient. Here, we present a saliency-guided approach that groups regions that potentially belong to the same object based on proximity and similarity of motion. We compare our results to object selection by thresholding saliency maps and a further attention-guided strategy.

PUBLICATION RECORD

  • Publication year

    2013

  • Venue

    arXiv.org

  • Publication date

    2013-07-22

  • Fields of study

    Computer Science, Engineering

  • Identifiers
    arXiv 1307.5710
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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