Motion Saliency Maps from Spatiotemporal Filtering

  • Authors:
  • Anna Belardinelli;Fiora Pirri;Andrea Carbone

  • Affiliations:
  • Dipartimento di Informatica e Sistemistica, Sapienza University of Rome,;Dipartimento di Informatica e Sistemistica, Sapienza University of Rome,;Dipartimento di Informatica e Sistemistica, Sapienza University of Rome,

  • Venue:
  • Attention in Cognitive Systems
  • Year:
  • 2009

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Abstract

For artificial systems acting and perceiving in a dynamic world a core ability is to focus on aspects of the environment that can be crucial for the task at hand. Perception in autonomous systems needs to be filtered by a biologically inspired selective ability, therefore attention in dynamic settings is becoming a key research issue. In this paper we present a model for motion salience map computation based on spatiotemporal filtering. We extract a measure of coherent motion energy and select by the center-surround mechanism relevant zones that accumulate most energy and therefore contrast with surroundings in a given time slot. The method was tested on synthetic and real video sequences, supporting biological plausibility.