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We propose a novel recurrent attentional structure to localize and recognize objects jointly. The network can learn to extract a sequence of local observations with detailed appearance and rough context, instead of sliding windows or…

Computer Vision and Pattern Recognition · Computer Science 2017-12-20 Jie Lyu , Zejian Yuan , Dapeng Chen

In an experiment involving semantic search, the visual movements of sample populations subjected to visual and aural input were tracked in a taskless paradigm. The probability distributions of saccades and fixations were obtained and…

Statistical Mechanics · Physics 2015-05-27 D. P. Shinde , Anita Mehta , R. K. Mishra

Research studies have shown that a large proportion of hazards remain unrecognized, which expose construction workers to unanticipated safety risks. Recent studies have also found that a strong correlation exists between viewing patterns of…

Computer Vision and Pattern Recognition · Computer Science 2019-02-05 Idris Jeelani , Khashayar Asadi , Hariharan Ramshankar , Kevin Han , Alex Albert

This study investigates how cinematographic techniques influence viewer perception and contribute to the objectification of women, utilizing eye-tracking data from 91 participants. They watched a sexualized music video (SV) known for…

Human-Computer Interaction · Computer Science 2025-04-15 Parth Maradia , Ayushi Agarwal , Srija Bhupathiraju , Kavita Vemuri

When searching a target in a natural scene, both the target's visual properties and similarity to the background influence whether (and how fast) humans are able to find it. However, thus far it has been unclear whether searchers adjust the…

Neurons and Cognition · Quantitative Biology 2018-02-13 Lars Oliver Martin Rothkegel , Heiko Herbert Schütt , Hans Arne Trukenbrod , Felix Alexander Wichmann , Ralf Engbert

Some visual search tasks require to memorize the location of stimuli that have been previously scanned. Considerations about the eye movements raise the question of how we are able to maintain a coherent memory, despite the frequent…

Neural and Evolutionary Computing · Computer Science 2016-08-16 Jérémy Fix , Julien Vitay , Nicolas Rougier

The anisotropic 2-point correlation function (2PCF) of galaxies measures pairwise clustering as a function of the pair separation's angle to the line of sight. The latter is often defined as either the angle bisector of the…

Cosmology and Nongalactic Astrophysics · Physics 2015-10-19 Zachary Slepian , Daniel J. Eisenstein

In this work we study the identification of spatial correlation in distributions of 2D scalar fields, presented across different forms of visual displays. We study simple visual displays that directly show color-mapped scalar fields, namely…

Human-Computer Interaction · Computer Science 2025-07-25 Yayan Zhao , Matthew Berger

Bottom-up and top-down, as well as low-level and high-level factors influence where we fixate when viewing natural scenes. However, the importance of each of these factors and how they interact remains a matter of debate. Here, we…

Neurons and Cognition · Quantitative Biology 2018-05-18 Heiko H. Schütt , Lars O. M. Rothkegel , Hans A. Trukenbrod , Ralf Engbert , Felix A. Wichmann

In climate studies, detecting spatial patterns that largely deviate from the sample mean still remains a statistical challenge. Although a Principal Component Analysis (PCA), or equivalently a Empirical Orthogonal Functions (EOF)…

Statistics Theory · Mathematics 2020-01-29 Alberto Bernacchia , Philippe Naveau

We present a novel visual attention tracking technique based on Shared Attention modeling. Our proposed method models the viewer as a participant in the activity occurring in the scene. We go beyond image salience and instead of only…

Computer Vision and Pattern Recognition · Computer Science 2016-09-02 Siavash Gorji , James J. Clark

Spatial confounding between the spatial random effects and fixed effects covariates has been recently discovered and showed that it may bring misleading interpretation to the model results. Solutions to alleviate this problem are based on…

Methodology · Statistics 2016-05-17 Marcos O. Prates , Erica C. Rodrigues , Renato M. Assunção

Spatial confounding is how is called the confounding between fixed and spatial random effects. It has been widely studied and it gained attention in the past years in the spatial statistics literature, as it may generate unexpected results…

The analysis of spatial point patterns that occur in the network domain have recently gained much attraction and various intensity functions and measures have been proposed. However, the linkage of spatial network statistics to regression…

Applications · Statistics 2016-07-25 Matthias Eckardt , Jorge Mateu

In many computer vision tasks, the relevant information to solve the problem at hand is mixed to irrelevant, distracting information. This has motivated researchers to design attentional models that can dynamically focus on parts of images…

Computer Vision and Pattern Recognition · Computer Science 2017-02-14 Loris Bazzani , Hugo Larochelle , Lorenzo Torresani

A natural way to improve the detection of objects is to consider the contextual constraints imposed by the detection of additional objects in a given scene. In this work, we exploit the spatial relations between objects in order to improve…

Computer Vision and Pattern Recognition · Computer Science 2018-10-19 Ehud Barnea , Ohad Ben-Shahar

Many events and policies (treatments) occur at specific spatial locations, with researchers interested in their effects on nearby units. I approach the spatial treatment setting from an experimental perspective: What ideal experiment would…

Econometrics · Economics 2026-04-27 Michael Pollmann

When humans view scenes without a specific task (free-viewing), they initially direct their eye movements toward the scene center and then fixate on people, text, objects being gazed at or grasped, and semantically meaningful regions. What…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Shravan Murlidaran , Ziqi Wen , Sana Shehabi , Miguel P. Eckstein

Making accurate inferences about other individuals' locus of attention is essential for human social interactions and will be important for AI to effectively interact with humans. In this study, we compare how a CNN (convolutional neural…

Computer Vision and Pattern Recognition · Computer Science 2021-04-20 Nicole X. Han , William Yang Wang , Miguel P. Eckstein

Accurate prediction of pedestrian trajectories is crucial for enhancing the safety of autonomous vehicles and reducing traffic fatalities involving pedestrians. While numerous studies have focused on modeling interactions among pedestrians…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Mohammad Ali Rezaei , Fardin Ayar , Ehsan Javanmardi , Manabu Tsukada , Mahdi Javanmardi