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Context mitigates crowding: Peripheral object recognition in real-world images.

Maarten W A Wijntjes1, Ruth Rosenholtz2

  • 1Perceptual Intelligence Lab, Industrial Design Engineering, Delft University of Technology, The Netherlands.

Cognition
|July 29, 2018
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Summary
This summary is machine-generated.

Object recognition in peripheral vision is impaired by segmentation. Real-world context is crucial, proving as informative as viewing the object alone, challenging traditional views of visual crowding.

Keywords:
ContextCrowdingIntegrationObject recognitionShrink-wrap

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Visual Perception

Background:

  • Object recognition is typically viewed as a process of segmenting objects from their surroundings and integrating features.
  • Visual crowding in peripheral vision has been attributed to a failure in restricting feature integration to object-specific elements.

Purpose of the Study:

  • To investigate the role of object segmentation and real-world context in peripheral object recognition.
  • To challenge the conventional understanding of visual crowding as a failure of segmentation.

Main Methods:

  • Hand-segmenting objects from their backgrounds to isolate them from their natural context.
  • Comparing recognition performance with segmented objects, objects in context, and context alone in peripheral vision experiments.

Main Results:

  • Manual segmentation of objects from their background impaired peripheral recognition compared to viewing objects in their natural context.
  • Contextual information alone was found to be as effective for recognition as viewing the object in isolation.
  • No benefit was observed when presenting context and segmented objects separately.

Conclusions:

  • The findings suggest that object recognition does not ideally operate on pre-segmented objects.
  • Visual crowding should not be understood as solely a failure to segment objects correctly.
  • Real-world context plays a fundamental and indispensable role in peripheral object recognition.