Biologically Plausible Neural Model for the Recognition of Biological Motion and Actions

Abstract

The visual recognition of complex movements and actions is crucial for communications and survival in many species. Remarkable sensitivity and robustness of biological motion perception have been demonstrated in psychophysical experiments. In recent years, neurons and cortical areas involved in action recognition have been identified in neurophysiological and imaging studies. However, the detailed neural mechanisms that underlie the recognition of such complex movement patterns remain largely unknown. This paper reviews the experimental results and summarizes them in terms of a biologically plausible neural model. The model is based on the key assumption that action recognition is based on learned prototypical patterns and exploits information from the ventral and dorsal pathway. The model makes specific predictions that motivate new experiments.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2002
Accession Number
ADA459682

Entities

People

  • Martin A. Giese
  • Tomaso Poggio

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Brain
  • Computer Vision
  • Detectors
  • Flow Fields
  • Information Processing
  • Information Systems
  • Neural Networks
  • Neurons
  • Object Recognition
  • Pattern Recognition
  • Recognition
  • Recurrent Neural Networks
  • Simulations
  • Three Dimensional
  • Two Dimensional
  • Visual Cortex

Readers

  • Computer Vision.
  • Neuroscience
  • Systems Analysis and Design