ArticleFrontiers in human neuroscience2017
How Well Can Saliency Models Predict Fixation Selection in Scenes Beyond Central Bias? A New Approach to Model Evaluation Using Generalized Linear Mixed Models.
Article in Frontiers in human neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- GridSamp: An open-source Python toolbox for grid sampling.Behavior research methods · 2026Article
- Directing gaze to maximize surface color information from natural scenes.Scientific reports · 2026Article
- No robust evidence for an effect of head-movement propensity on central bias in head-constrained scene viewing, despite an effect on fixation duration.Journal of vision · 2025Article
- A robotics-inspired scanpath model reveals the importance of uncertainty and semantic object cues for gaze guidance in dynamic scenes.Journal of vision · 2025Article
- The fundamentals of eye tracking part 4: Tools for conducting an eye tracking study.Behavior research methods · 2025Article
- The Visual Integration of Semantic and Spatial Information of Objects in Naturalistic Scenes (VISIONS) database: attentional, conceptual, and perceptual norms.Behavior research methods · 2025Article
- Scene semantics affects allocentric spatial coding for action in naturalistic (virtual) environments.Scientific reports · 2024Article
- Objects are selected for attention based upon meaning during passive scene viewing.Psychonomic bulletin & review · 2023Article
- Objects guide human gaze behavior in dynamic real-world scenes.PLoS computational biology · 2023Article
- Pseudoneglect during object search in naturalistic scenes.Experimental brain research · 2023Article
- Free viewing biases for complex scenes in preschoolers and adults.Scientific reports · 2023Article
- Visual attention during seeing for speaking in healthy aging.Psychology and aging · 2023Article
- Look at what I can do: Object affordances guide visual attention while speakers describe potential actions.Attention, perception & psychophysics · 2022Article
- Rapid Extraction of the Spatial Distribution of Physical Saliency and Semantic Informativeness from Natural Scenes in the Human Brain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- Meaning and expected surfaces combine to guide attention during visual search in scenes.Journal of vision · 2021Article
- Deep saliency models learn low-, mid-, and high-level features to predict scene attention.Scientific reports · 2021Article
- Looking for Semantic Similarity: What a Vector-Space Model of Semantics Can Tell Us About Attention in Real-World Scenes.Psychological science · 2021Article
- Glimpse: A Gaze-Based Measure of Temporal Salience.Sensors (Basel, Switzerland) · 2021Article
- The effect of target salience and size in visual search within naturalistic scenes under degraded vision.Journal of vision · 2021Article
- Salience-based object prioritization during active viewing of naturalistic scenes in young and older adults.Scientific reports · 2020Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Since the turn of the millennium, a large number of computational models of visual salience have been put forward. How best to evaluate a given model's ability to predict where human observers fixate in images of real-world scenes remains an open research question. Assessing the role of spatial biases is a challenging issue; this is particularly true when we consider the tendency for high-salience items to appear in the image center, combined with a tendency to look straight ahead ("central bias"). This problem is further exacerbated in the context of model comparisons, because some-but not all-models implicitly or explicitly incorporate a center preference to improve performance. To address this and other issues, we propose to combine
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