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Related Experiment Videos

Dissociating stimulus information from internal representation--a case study in object recognition.

Z Liu1, D Kersten, D C Knill

  • 1NEC Research Institute, Princeton, NJ 08540, USA. zliu@research.nj.nec.com

Vision Research
|May 26, 1999
PubMed
Summary
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Human object recognition depends on memory and visual input. This study shows that simpler objects provide more visual information, improving recognition performance and suggesting internal representations are key.

Area of Science:

  • Cognitive Psychology
  • Computational Neuroscience
  • Computer Vision

Background:

  • Human object recognition relies on internal memory and external stimulus information.
  • The contribution of stimulus information to recognition has been underestimated.
  • Object representation is often conflated with recognition performance.

Purpose of the Study:

  • To quantify stimulus information for objects of varying complexity.
  • To investigate the interplay between stimulus information and internal representations in object recognition.
  • To determine the factors influencing human object discrimination performance.

Main Methods:

  • Quantified stimulus information for three object classes (unconnected balls, balls with lines, balls with cylinders).

Related Experiment Videos

  • Assessed human performance in an object discrimination task.
  • Calculated recognition efficiencies relative to ideal observers, accounting for image information.

    • Main Results:

    • Subject performance improved with decreasing object complexity.
    • Stimulus information increased with decreasing object complexity.
    • Subjects were more efficient in recognizing less complex objects when image information was considered.

    Conclusions:

    • Object recognition performance is influenced by both internal representations and stimulus information.
    • Differences in performance across object classes are partly due to learned internal representations.
    • Quantitative analysis of stimulus information is crucial for understanding object recognition.