scholarly journals Scanning activity of elite football players in 11 vs. 11 match play: An eye-tracking analysis on the duration and visual information of scanning

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0244118
Author(s):  
Karl Marius Aksum ◽  
Lars Brotangen ◽  
Christian Thue Bjørndal ◽  
Lukas Magnaguagno ◽  
Geir Jordet
Keyword(s):  
Visual Perception ◽  
Eye Tracking ◽  
Visual Information ◽  
Video Frame ◽  
Practical Applications ◽  
Area Of Interest ◽  
Information Number ◽  
Scanning Behavior ◽  
Game Environment ◽  
The Moment

Visual perception in football (“soccer” in the U.S.) is increasingly becoming a key area of interest for researchers and practitioners. This exploratory case study investigated a sub-set of visual perception, namely visual exploratory scanning. The aim of this study was to examine the scanning of four elite football midfield players in an 11 vs. 11 real-game environment using mobile eye-tracking technology. More specifically, we measured the duration and information (number of teammates and opponents) of the players’ scanning behavior. The results showed that the players’ scanning duration was influenced by the ball context and the action undertaken with the ball at the moment of scan initiation. Furthermore, fixations were found in only 2.3% of the scans. Additionally, the results revealed that the stop point is the most information-rich part of a scan and that the players had more opponents than teammates inside their video frame during scans. Practical applications and further research recommendations are presented.

Evaluation of Situations Causing Split of Attention in Multimedia Learning Environments via Eye-Tracking Method

2015 ◽  
pp. 337-367 ◽  
Author(s):  
Duygu Mutlu-Bayraktar ◽  
Servet Bayram
Keyword(s):  
Eye Tracking ◽  
Learning Environments ◽  
Visual Information ◽  
Multimedia Learning ◽  
Heat Maps ◽  
Tracking Method ◽  
Attention Effect ◽  
Area Of Interest ◽  
Video Images ◽  
Multimedia Environments

In this chapter, situations that can cause split of attention in multimedia environments were determined via eye tracking method. Fixation numbers, heat maps and area of interest of learners were analyzed. As a result of these analyses, design suggestions were determined for multimedia environments to provide focusing attention to content without split attention effect. Visual and auditory resources should be provided simultaneously. Visual information should be supported with auditory expression instead of texts. Images such as videos, pictures and texts should not be presented on the same screen. Texts provided with pictures should be presented via integration to each other instead of separate presentation of text and picture. Texts provided with videos should be presented via integration to each other instead of separate presentation of text and video. Images should be given via marking important points on images to increase attention.

Evaluation of Situations Causing Split of Attention in Multimedia Learning Environments via Eye-Tracking Method

2018 ◽  
pp. 348-372
Author(s):  
Duygu Mutlu-Bayraktar ◽  
Servet Bayram
Keyword(s):  
Eye Tracking ◽  
Learning Environments ◽  
Visual Information ◽  
Multimedia Learning ◽  
Heat Maps ◽  
Tracking Method ◽  
Attention Effect ◽  
Area Of Interest ◽  
Video Images ◽  
Multimedia Environments

In this chapter, situations that can cause split of attention in multimedia environments were determined via eye tracking method. Fixation numbers, heat maps and area of interest of learners were analyzed. As a result of these analyses, design suggestions were determined for multimedia environments to provide focusing attention to content without split attention effect. Visual and auditory resources should be provided simultaneously. Visual information should be supported with auditory expression instead of texts. Images such as videos, pictures and texts should not be presented on the same screen. Texts provided with pictures should be presented via integration to each other instead of separate presentation of text and picture. Texts provided with videos should be presented via integration to each other instead of separate presentation of text and video. Images should be given via marking important points on images to increase attention.

Eye movements in sports research and practice: Immersive technologies as optimal environments for the study of gaze behaviour

2020 ◽  
Author(s):  
David Harris ◽  
Mark Wilson ◽  
Tim Holmes ◽  
Toby de Burgh ◽  
Samuel James Vine
Keyword(s):  
Virtual Reality ◽  
Eye Movements ◽  
Eye Tracking ◽  
Visual Information ◽  
Successful Performance ◽  
Experimental Control ◽  
Research And Practice ◽  
Gaze Behaviour ◽  
Immersive Technologies

Head-mounted eye tracking has been fundamental for developing an understanding of sporting expertise, as the way in which performers sample visual information from the environment is a major determinant of successful performance. There is, however, a long running tension between the desire to study realistic, in-situ gaze behaviour and the difficulties of acquiring accurate ocular measurements in dynamic and fast-moving sporting tasks. Here, we describe how immersive technologies, such as virtual reality, offer an increasingly compelling approach for conducting eye movement research in sport. The possibility of studying gaze behaviour in representative and realistic environments, but with high levels of experimental control, could enable significant strides forward for eye tracking in sport and improve understanding of how eye movements underpin sporting skills. By providing a rationale for virtual reality as an optimal environment for eye tracking research, as well as outlining practical considerations related to hardware, software and data analysis, we hope to guide researchers and practitioners in the use of this approach.

Deterministic Deployment for Wireless Image Sensor Nodes

2014 ◽  
Vol 8 (1) ◽  
pp. 668-674
Author(s):  
Junguo Zhang ◽  
Yutong Lei ◽  
Fantao Lin ◽  
Chen Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Visual Information ◽  
Image Sensor ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Effective Coverage ◽  
Area Of Interest ◽  
Key Issues

Wireless sensor networks composed of camera enabled source nodes can provide visual information of an area of interest, potentially enriching monitoring applications. The node deployment is one of the key issues in the application of wireless sensor networks. In this paper, we take the effective coverage and connectivity as the evaluation indices to analyze the effect of the perceivable angle and the ratio of communication radius and sensing radius for the deterministic circular deployment. Experimental results demonstrate that the effective coverage area of the triangle deployment is the largest when using the same number of nodes. When the nodes are deployed in the same monitoring area in the premise of ensuring connectivity, rhombus deployment is optimal when √2 < rc / rs < √3 . The research results of this paper provide an important reference for the deployment of the image sensor networks with the given parameters.

Bullying, School Violence, and Climate in Evolving Contexts

2018 ◽  
Author(s):  
Ron Avi Astor ◽  
Rami Benbenisthty
Keyword(s):  
School Violence ◽  
School Safety ◽  
Media Coverage ◽  
Large Scale ◽  
Ecological Model ◽  
Empirical Studies ◽  
Practical Applications ◽  
Teacher Student ◽  
Area Of Interest ◽  
New Research

Since 2005, the bullying, school violence, and school safety literatures have expanded dramatically in content, disciplines, and empirical studies. However, with this massive expansion of research, there is also a surprising lack of theoretical and empirical direction to guide efforts on how to advance our basic science and practical applications of this growing scientific area of interest. Parallel to this surge in interest, cultural norms, media coverage, and policies to address school safety and bullying have evolved at a remarkably quick pace over the past 13 years. For example, behaviors and populations that just a decade ago were not included in the school violence, bullying, and school safety discourse are now accepted areas of inquiry. These include, for instance, cyberbullying, sexting, social media shaming, teacher–student and student–teacher bullying, sexual harassment and assault, homicide, and suicide. Populations in schools not previously explored, such as lesbian, gay, bisexual, transgender, and queer students and educators and military- and veteran-connected students, become the foci of new research, policies, and programs. As a result, all US states and most industrialized countries now have a complex quilt of new school safety and bullying legislation and policies. Large-scale research and intervention funding programs are often linked to these policies. This book suggests an empirically driven unifying model that brings together these previously distinct literatures. This book presents an ecological model of school violence, bullying, and safety in evolving contexts that integrates all we have learned in the 13 years, and suggests ways to move forward.

Visual Anticipatory Information Modulates Multisensory Interactions of Artificial Audiovisual Stimuli

2010 ◽  
Vol 22 (7) ◽  
pp. 1583-1596 ◽  
Author(s):  
Jean Vroomen ◽  
Jeroen J. Stekelenburg
Keyword(s):  
Visual Information ◽  
Speech Sound ◽  
Human Action ◽  
Visual Signal ◽  
Multisensory Interactions ◽  
Temporal Occurrence ◽  
Audiovisual Stimuli ◽  
The Moment ◽  
Integrative Processing ◽  
Audiovisual Interaction

The neural activity of speech sound processing (the N1 component of the auditory ERP) can be suppressed if a speech sound is accompanied by concordant lip movements. Here we demonstrate that this audiovisual interaction is neither speech specific nor linked to humanlike actions but can be observed with artificial stimuli if their timing is made predictable. In Experiment 1, a pure tone synchronized with a deformation of a rectangle induced a smaller auditory N1 than auditory-only presentations if the temporal occurrence of this audiovisual event was made predictable by two moving disks that touched the rectangle. Local autoregressive average source estimation indicated that this audiovisual interaction may be related to integrative processing in auditory areas. When the moving disks did not precede the audiovisual stimulus—making the onset unpredictable—there was no N1 reduction. In Experiment 2, the predictability of the leading visual signal was manipulated by introducing a temporal asynchrony between the audiovisual event and the collision of moving disks. Audiovisual events occurred either at the moment, before (too “early”), or after (too “late”) the disks collided on the rectangle. When asynchronies varied from trial to trial—rendering the moving disks unreliable temporal predictors of the audiovisual event—the N1 reduction was abolished. These results demonstrate that the N1 suppression is induced by visual information that both precedes and reliably predicts audiovisual onset, without a necessary link to human action-related neural mechanisms.

Emulsion Stability Evaluation Using Fractal Dimensions Approach

2007 ◽  
Vol 555 ◽  
pp. 177-182 ◽  
Author(s):  
Snezana Pašalić ◽  
P.B. Jovanić ◽  
B. Bugarski
Keyword(s):  
Visual Information ◽  
Emulsion Stability ◽  
Fractal Dimensions ◽  
Ccd Camera ◽  
Point Of View ◽  
Stable Region ◽  
Stability Evaluation ◽  
Water Emulsion ◽  
The Moment ◽  
Oil In Water Emulsion

There are many developed strategies for evaluating emulsion stability, aimed at determining the life circle of emulsions. Most of them are based on rheological properties of emulsions. There are, however, very few based on direct emulsion observations. In this paper we present a developed method for the emulsion stability evaluation by direct observation of optical emulsion properties. We propose the fractal dimension approach as a stability quantification measure. The method is based on the measure of emulsion transmittance properties, which are directly dependent on the emulsion stability at the moment of measurement. The oil in water emulsion was used as a test emulsion. The system is classified as stable emulsion and our intention was to find the moment when it starts to break. Emulsion transmittance properties were measure applying a system for acquisition of visual information, which is based on a CCD camera and a fast PC configuration equipped with the capturing software. The acquired sets of visual information were analyzed by the OZARIA software package. The fractal dimensions were determined by the box counting method. For these experiments, 100 boxes of different sizes were used. Experimental emulsions were measured after 7, 14, 21 and 28 days from the moment of creation. A slight increase in fractal dimensions was observed, which indicates that the emulsions are still in the stable region, or from the fractal point of view emulsion are still regular and no significant irregularities were observed. From the first experiments the applied methodology proved to be sensitive enough to be used for emulsions stability evaluation.

scholarly journals Domain-Adversarial Training of Self-Attention-Based Networks for Land Cover Classification Using Multi-Temporal Sentinel-2 Satellite Imagery

2021 ◽  
Vol 13 (13) ◽  
pp. 2564
Author(s):  
Mauro Martini ◽  
Vittorio Mazzia ◽  
Aleem Khaliq ◽  
Marcello Chiaberge
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Domain Adaptation ◽  
Learning Approaches ◽  
Atmospheric Conditions ◽  
Practical Applications ◽  
Area Of Interest ◽  
Multi Temporal ◽  
Significant Performance ◽  
Adversarial Training

The increasing availability of large-scale remote sensing labeled data has prompted researchers to develop increasingly precise and accurate data-driven models for land cover and crop classification (LC&CC). Moreover, with the introduction of self-attention and introspection mechanisms, deep learning approaches have shown promising results in processing long temporal sequences in the multi-spectral domain with a contained computational request. Nevertheless, most practical applications cannot rely on labeled data, and in the field, surveys are a time-consuming solution that pose strict limitations to the number of collected samples. Moreover, atmospheric conditions and specific geographical region characteristics constitute a relevant domain gap that does not allow direct applicability of a trained model on the available dataset to the area of interest. In this paper, we investigate adversarial training of deep neural networks to bridge the domain discrepancy between distinct geographical zones. In particular, we perform a thorough analysis of domain adaptation applied to challenging multi-spectral, multi-temporal data, accurately highlighting the advantages of adapting state-of-the-art self-attention-based models for LC&CC to different target zones where labeled data are not available. Extensive experimentation demonstrated significant performance and generalization gain in applying domain-adversarial training to source and target regions with marked dissimilarities between the distribution of extracted features.

Sign in / Sign up

Export Citation Format

Share Document