AI Article Synopsis

  • Recent research explores how low-level color features influence visual attention, but existing studies only show correlations without revealing mechanisms.
  • The study uses eye-tracking of color-normal and deuteranope participants viewing rainforest images, finding that removing red-green contrast significantly affects fixation behavior in color-normal individuals.
  • The results suggest that while red-green color information plays a key role in guiding attention, the processing of color information occurs in a way that is not limited to specific color axes, indicating a more generalized approach to evaluating colors.

Article Abstract

Recent research indicates a direct relationship between low-level color features and visual attention under natural conditions. However, the design of these studies allows only correlational observations and no inference about mechanisms. Here we go a step further to examine the nature of the influence of color features on overt attention in an environment in which trichromatic color vision is advantageous. We recorded eye-movements of color-normal and deuteranope human participants freely viewing original and modified rainforest images. Eliminating red-green color information dramatically alters fixation behavior in color-normal participants. Changes in feature correlations and variability over subjects and conditions provide evidence for a causal effect of red-green color-contrast. The effects of blue-yellow contrast are much smaller. However, globally rotating hue in color space in these images reveals a mechanism analyzing color-contrast invariant of a specific axis in color space. Surprisingly, in deuteranope participants we find significantly elevated red-green contrast at fixation points, comparable to color-normal participants. Temporal analysis indicates that this is due to compensatory mechanisms acting on a slower time scale. Taken together, our results suggest that under natural conditions red-green color information contributes to overt attention at a low-level (bottom-up). Nevertheless, the results of the image modifications and deuteranope participants indicate that evaluation of color information is done in a hue-invariant fashion.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3079176PMC
http://dx.doi.org/10.3389/fnhum.2011.00036DOI Listing

Publication Analysis

Top Keywords

color features
12
color
8
natural conditions
8
overt attention
8
red-green color
8
color-normal participants
8
color space
8
deuteranope participants
8
participants
5
correlation color
4

Similar Publications

Background: In data-sparse areas such as health care, computer scientists aim to leverage as much available information as possible to increase the accuracy of their machine learning models' outputs. As a standard, categorical data, such as patients' gender, socioeconomic status, or skin color, are used to train models in fusion with other data types, such as medical images and text-based medical information. However, the effects of including categorical data features for model training in such data-scarce areas are underexamined, particularly regarding models intended to serve individuals equitably in a diverse population.

View Article and Find Full Text PDF

The forensic examination of AIGC(Artificial Intelligence Generated Content) faces poses a contemporary challenge within the realm of color image forensics. A myriad of artificially generated faces by AIGC encompasses both global and local manipulations. While there has been noteworthy progress in the forensic scrutiny of fake faces, current research primarily focuses on the isolated detection of globally and locally manipulated fake faces, thus lacking a universally effective detection methodology.

View Article and Find Full Text PDF

Previous research has shown that, when multiple similar items are maintained in working memory, recall precision declines. Less is known about how heterogeneous sets of items across different features within and between modalities impact recall precision. In two experiments, we investigated modality (Experiment 1, n = 79) and feature-specific (Experiment 2, n = 154) load effects on working memory performance.

View Article and Find Full Text PDF

Machine learning reveals the dynamic importance of accessory sequences for outbreak clustering.

mBio

January 2025

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada.

Unlabelled: Bacterial typing at whole-genome scales is now feasible owing to decreasing costs in high-throughput sequencing and the recent advances in computation. The unprecedented resolution of whole-genome typing is achieved by genotyping the variable segments of bacterial genomes that can fluctuate significantly in gene content. However, due to the transient and hypervariable nature of many accessory elements, the value of the added resolution in outbreak investigations remains disputed.

View Article and Find Full Text PDF

Current challenges in tissue engineering include creation of extracellular environments that support and interact with cells using biochemical, mechanical, and structural cues. Spatial control over these cues is currently limited due to a lack of suitable fabrication techniques. This study introduces Xolography, an emerging dual-color light-sheet volumetric printing technology, to achieve control over structural and mechanical features for hydrogel-based photoresins at micro- to macroscale while printing within minutes.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!