scholarly journals Gaze Patterns and Visual Salience in Change Detection of Natural Scenes

2010 ◽  
Vol 10 (7) ◽  
pp. 169-169 ◽  
Author(s):  
T. W. Boyer ◽  
C. Yu ◽  
T. Smith ◽  
B. I. Bertenthal
Keyword(s):  
Change Detection ◽  
Natural Scenes ◽  
Visual Salience ◽  
Gaze Patterns

scholarly journals Low-level visual saliency does not predict change detection in natural scenes

2007 ◽  
Vol 7 (10) ◽  
pp. 3 ◽  
Author(s):  
Jonathan A. Stirk ◽  
Geoffrey Underwood
Keyword(s):  
Change Detection ◽  
Visual Saliency ◽  
Natural Scenes ◽  
Low Level

scholarly journals Attention in natural scenes: Affective-motivational factors guide gaze independently of visual salience

2017 ◽  
Vol 133 ◽  
pp. 161-175 ◽  
Author(s):  
Judith Schomaker ◽  
Daniel Walper ◽  
Bianca C. Wittmann ◽  
Wolfgang Einhäuser
Keyword(s):  
Motivational Factors ◽  
Natural Scenes ◽  
Visual Salience

scholarly journals Neurally-constrained modeling of human gaze strategies in a change blindness task

2021 ◽  
Vol 17 (8) ◽  
pp. e1009322
Author(s):  
Akshay Jagatap ◽  
Simran Purokayastha ◽  
Hritik Jain ◽  
Devarajan Sridharan
Keyword(s):  
Change Detection ◽  
Mechanistic Model ◽  
Change Blindness ◽  
Success Rates ◽  
Posterior Odds ◽  
Gaze Patterns ◽  
Ratio Rule ◽  
Scan Paths ◽  
Sequential Probability ◽  
Strategies For Change

Despite possessing the capacity for selective attention, we often fail to notice the obvious. We investigated participants’ (n = 39) failures to detect salient changes in a change blindness experiment. Surprisingly, change detection success varied by over two-fold across participants. These variations could not be readily explained by differences in scan paths or fixated visual features. Yet, two simple gaze metrics–mean duration of fixations and the variance of saccade amplitudes–systematically predicted change detection success. We explored the mechanistic underpinnings of these results with a neurally-constrained model based on the Bayesian framework of sequential probability ratio testing, with a posterior odds-ratio rule for shifting gaze. The model’s gaze strategies and success rates closely mimicked human data. Moreover, the model outperformed a state-of-the-art deep neural network (DeepGaze II) with predicting human gaze patterns in this change blindness task. Our mechanistic model reveals putative rational observer search strategies for change detection during change blindness, with critical real-world implications.

scholarly journals Effects of scene inversion on change detection of targets matched for visual salience

10.1167/3.1.1 ◽  
2003 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
Todd A. Kelley ◽  
Marvin M. Chun ◽  
Kao-Ping Chua
Keyword(s):  
Change Detection ◽  
Visual Salience

Iconic memory for natural scenes: Evidence using a modified change-detection procedure

2015 ◽  
Vol 23 (7) ◽  
pp. 917-938 ◽  
Author(s):  
Jason Clarke ◽  
Arien Mack
Keyword(s):  
Change Detection ◽  
Iconic Memory ◽  
Natural Scenes

scholarly journals Using V1-Based Models for Change Detection in Natural Scenes

2014 ◽  
Vol 14 (10) ◽  
pp. 372-372
Author(s):  
P. Y. Chua ◽  
K. Kwok
Keyword(s):  
Change Detection ◽  
Natural Scenes

Change Detection in Natural Scenes Using Laser Range Measurements from a Mobile Robot

1993 ◽  
Vol 26 (1) ◽  
pp. 71-76 ◽  
Author(s):  
P.L. Klöör ◽  
P. Lunquist ◽  
P. Ohlsson ◽  
J. Nygårds ◽  
Å. Wernersson
Keyword(s):  
Mobile Robot ◽  
Change Detection ◽  
Natural Scenes ◽  
Laser Range ◽  
Range Measurements
Sign in / Sign up

Export Citation Format

Share Document