A Neural Model Combining Attentional Orienting to Object Recognition: Preliminary Explorations on the Interplay Between Where and What

Abstract

We propose a model of primate vision that integrates both an attentional orienting ("where") pathway and an object recognition ("what") pathway. The fast visual attention front-end rapidly selects the few most conspicuous image locations, and the slower object recognition back-end identifies objects at the selected locations. The model is applied to classical visual search tasks, consisting of finding a specific target among an array of distracting visual patterns (e.g., a circle among many squares). The encouraging results obtained, in which substantial speedup is achieved by the combined attention- recognition model while maintaining good recognition performance compared to an exhaustive search, suggest that the biologically-inspired architecture proposed represents an efficient solution to the difficult problem of rapid scene analysis.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411203

Entities

People

  • Florence Miau
  • Laurent Itti

Organizations

  • University of Southern California

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computations
  • Computer Science
  • Computer Vision
  • Computers
  • Detection
  • False Alarms
  • High Resolution
  • Image Recognition
  • Images
  • Low Resolution
  • Military Vehicles
  • Object Recognition
  • Recognition
  • Shape
  • Target Detection
  • Translations

Fields of Study

  • Computer science

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computer Vision.
  • Distributed Systems and Data Platform Development