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Related Concept Videos

Perceptual Constancy01:12

Perceptual Constancy

Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
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Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
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Role of Shaping in Operant Conditioning

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Purposive Learning

E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a bonus...

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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

Perceptual learning of object shape.

Doruk Gölcü1, Charles D Gilbert

  • 1The Rockefeller University, New York, New York 10065, USA.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|October 30, 2009
PubMed
Summary
This summary is machine-generated.

Human object recognition involves learning object components, not holistic shapes. This study shows visual search training improves identification by encoding individual features, crucial for recognizing novel objects.

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Computer Vision

Background:

  • Object recognition relies on internal representations of familiar shapes.
  • Perceptual learning paradigms are used to investigate visual object identification.
  • Understanding how humans encode object features is key to artificial intelligence.

Purpose of the Study:

  • To explore the specific features human observers utilize for object identification.
  • To determine if objects are represented holistically or by individual components during learning.
  • To investigate the role of object components in recognition through transfer learning.

Main Methods:

  • Utilized a perceptual learning paradigm involving visual search.
  • Trained human subjects to identify a target object among distractors.
  • Measured learning transfer to novel objects sharing components with the trained object.

Main Results:

  • Learning transferred to novel objects sharing components, indicating feature-based encoding.
  • Training improved identification of objects based on shared components.
  • Transfer occurred for multiple components, suggesting joint involvement for full recognition.

Conclusions:

  • Objects are encoded by their individual components rather than holistically during visual learning.
  • Component-based representation is crucial for recognizing familiar and novel objects.
  • Full object recognition likely requires the integrated processing of multiple components.