ArticlePloS one2015
Visual Saliency Prediction and Evaluation across Different Perceptual Tasks.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Searching for meaning: Local scene semantics guide attention during natural visual search in scenes.Quarterly journal of experimental psychology (2006) · 2023Article
- Salience-based object prioritization during active viewing of naturalistic scenes in young and older adults.Scientific reports · 2020Article
- When scenes speak louder than words: Verbal encoding does not mediate the relationship between scene meaning and visual attention.Memory & cognition · 2020Article
- Center bias outperforms image salience but not semantics in accounting for attention during scene viewing.Attention, perception & psychophysics · 2020Article
- Center Bias Does Not Account for the Advantage of Meaning Over Salience in Attentional Guidance During Scene Viewing.Frontiers in psychology · 2020Article
- The role of meaning in attentional guidance during free viewing of real-world scenes.Acta psychologica · 2019Article
- Meaning guides attention during scene viewing, even when it is irrelevant.Attention, perception & psychophysics · 2019Article
- How Well Can Saliency Models Predict Fixation Selection in Scenes Beyond Central Bias? A New Approach to Model Evaluation Using Generalized Linear Mixed Models.Frontiers in human neuroscience · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Saliency maps produced by different algorithms are often evaluated by comparing output to fixated image locations appearing in human eye tracking data. There are challenges in evaluation based on fixation data due to bias in the data. Properties of eye movement patterns that are independent of image content may limit the validity of evaluation results, including spatial bias in fixation data. To address this problem, we present modeling and evaluation results for data derived from different perceptual tasks related to the concept of saliency. We also present a novel approach to benchmarking to deal with some of the challenges posed by spatial bias. The results presented establish the value of alternatives to fixation data to drive improvement and development of models. We also demonstrate an approach to approximate the output of alternative perceptual tasks based on computational saliency and/or eye gaze data. As a whole, this work presents novel benchmarking results and methods, establishes a new performance baseline for perceptual tasks that provide an alternative window into visual saliency, and demonstrates the capacity for saliency to serve in approximating human behaviour for one visual task given data from another.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.