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Related Experiment Video

Updated: Jun 19, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

Published on: December 15, 2023

Contrast- and illumination-invariant object recognition from active sensation.

Ingo Rentschler¹, Erol Osman, Martin Jüttner

¹Institute of Medical Psychology, University of Munich, Munich, Germany. Ingo.Rentschler@med.uni-muenchen.de

|October 10, 2009

Summary

Visual recognition of objects is not invariant to contrast reversal. Prior knowledge from active sensation can restore invariance for non-face objects, suggesting task-dependent learning influences object representations.

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Published on: August 1, 2018

Area of Science:

Cognitive psychology
Neuroscience
Computer vision

Background:

Previous research suggested contrast reversal primarily impairs face recognition.
The generalizability of this effect to non-face objects remained unclear.

Purpose of the Study:

To investigate whether visual recognition of non-face objects is invariant to contrast reversal and illumination changes.
To determine if prior object knowledge can mitigate the effects of contrast reversal and learning.

Main Methods:

Priming experiments
Supervised category learning tasks
Generalization tests
Active sensation for prior object knowledge

Main Results:

Object recognition showed no general invariance to contrast reversal or illumination changes.
Prior object knowledge from active sensation restored invariance and reduced learning effects.
Recognition variability correlated with rendering conditions.

Conclusions:

Object recognition is not inherently invariant to contrast reversal or illumination.
Learned object representations are task-dependent and influence contrast invariance.
Active sensation plays a crucial role in achieving robust object recognition under varying conditions.