scholarly journals Diagnostic Features for Visual Object Recognition in Humans

2019 ◽  
Vol 19 (10) ◽  
pp. 30d
Author(s):  
Quentin Wohlfarth ◽  
Martin Arguin
Keyword(s):  
Object Recognition ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Diagnostic Features

scholarly journals Feature blindness: a challenge for understanding and modelling visual object recognition

2021 ◽  
Author(s):  
Gaurav Malhotra ◽  
Marin Dujmovic ◽  
Jeffrey S Bowers
Keyword(s):  
Object Recognition ◽  
Statistical Inference ◽  
Computational Cost ◽  
Fundamental Difference ◽  
Human Vision ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Global Features ◽  
Diagnostic Features ◽  
Inference Models

A central problem in vision sciences is to understand how humans recognise objects under novel viewing conditions. Recently, statistical inference models such as Convolutional Neural Networks (CNNs) seem to have reproduced this ability by incorporating some architectural constraints of biological vision systems into machine learning models. This has led to the proposal that, like CNNs, humans solve the problem of object recognition by performing a statistical inference over their observations. This hypothesis remains difficult to test as models and humans learn in vastly different environments. Accordingly, any differences in performance could be attributed to the training environment rather than reflect any fundamental difference between statistical inference models and human vision. To overcome these limitations, we conducted a series of experiments and simulations where humans and models had no prior experience with the stimuli. The stimuli contained multiple features that varied in the extent to which they predicted category membership. We observed that human participants frequently ignored features that were highly predictive and clearly visible. Instead, they learned to rely on global features such as colour or shape, even when these features were not the most predictive. When these features were absent they failed to learn the task entirely. By contrast, ideal inference models as well as CNNs always learned to categorise objects based on the most predictive feature. This was the case even when the CNN was pre-trained to have a shape-bias and the convolutional backbone was frozen. These results highlight a fundamental difference between statistical inference models and humans: while statistical inference models such as CNNs learn most diagnostic features with little regard for the computational cost of learning these features, humans are highly constrained by their limited cognitive capacities which results in a qualitatively different approach to object recognition.

Developmental Trajectory of Visual Object Recognition Revealed by fMRI

2007 ◽  
Author(s):  
K. Suzanne Scherf ◽  
Marlene Behrmann ◽  
Kate Humphreys ◽  
Beatriz Luna
Keyword(s):  
Object Recognition ◽  
Developmental Trajectory ◽  
Visual Object ◽  
Visual Object Recognition

scholarly journals Haptic object recognition based on shape relates to visual object recognition ability

2021 ◽  
Author(s):  
Jason K. Chow ◽  
Thomas J. Palmeri ◽  
Isabel Gauthier
Keyword(s):  
Object Recognition ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Recognition Ability ◽  
Haptic Object

Visual Object Recognition: Do We Know More Now Than We Did 20 Years Ago?

2007 ◽  
Vol 58 (1) ◽  
pp. 75-96 ◽  
Author(s):  
Jessie J. Peissig ◽  
Michael J. Tarr
Keyword(s):  
Object Recognition ◽  
Visual Object ◽  
Visual Object Recognition

Mechanisms of visual object recognition studied in monkeys

2000 ◽  
Vol 13 (2-3) ◽  
pp. 147-163 ◽  
Author(s):  
Keiji Tanaka
Keyword(s):  
Object Recognition ◽  
Visual Object ◽  
Visual Object Recognition

Quantifying the role of context in visual object recognition

2013 ◽  
Vol 22 (1) ◽  
pp. 30-56 ◽  
Author(s):  
Elan Barenholtz
Keyword(s):  
Object Recognition ◽  
Visual Object ◽  
Visual Object Recognition

Category-specificity in visual object recognition

Cognition ◽  
2009 ◽  
Vol 111 (3) ◽  
pp. 281-301 ◽  
Author(s):  
Christian Gerlach
Keyword(s):  
Object Recognition ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Category Specificity

scholarly journals Developmental changes in visual object recognition between 18 and 24 months of age

2009 ◽  
Vol 12 (1) ◽  
pp. 67-80 ◽  
Author(s):  
Alfredo F. Pereira ◽  
Linda B. Smith
Keyword(s):  
Object Recognition ◽  
Developmental Changes ◽  
Visual Object ◽  
Visual Object Recognition
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