Pop-out vs. Glue: A Study on the pre-attentive and focused attention stages in Visual Search tasks
December 14, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Hendrik Beukelman, Wilder C. Rodrigues
arXiv ID
2412.12198
Category
q-bio.NC
Cross-listed
cs.AI,
stat.ME
Citations
0
Venue
arXiv.org
Last Checked
3 months ago
Abstract
This study explores visual search asymmetry and the detection process between parallel and serial search strategies, building upon Treisman's Feature Integration Theory [3]. Our experiment examines how easy it is to locate an oblique line among vertical distractors versus a vertical line among oblique distractors, a framework previously validated by Treisman & Gormican (1988) [4] and Gupta et al. (2015) [1]. We hypothesised that an oblique target among vertical lines would produce a perceptual 'pop-out' effect, allowing for faster, parallel search, while the reverse condition would require serial search strategy. Seventy-eight participants from Utrecht University engaged in trials with varied target-distractor orientations and number of items. We measured reaction times and found a significant effect of target type on search speed: oblique targets were identified more quickly, reflecting 'pop-out' behaviour, while vertical targets demanded focused attention ('glue phase'). Our results align with past findings, supporting our hypothesis on search asymmetry and its dependency on distinct visual features. Future research could benefit from eye-tracking and neural network analysis, particularly for identifying the neural processing of visual features in both parallel and serial search conditions.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β q-bio.NC
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
SuperSpike: Supervised learning in multi-layer spiking neural networks
R.I.P.
π»
Ghosted
Generic decoding of seen and imagined objects using hierarchical visual features
R.I.P.
π»
Ghosted
Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future
R.I.P.
π»
Ghosted
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology
R.I.P.
π»
Ghosted
Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted