Gaze behavior and visual attention model when turning in virtual environments

Hillaire, Sébastien; Lécuyer, Anatole; Breton, Gaspard; Corte, Tony Regia

doi:10.1145/1643928.1643941

Cited by 13 publications

(19 citation statements)

References 13 publications

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“…As future work, Lee et al [6] suggested to take into account the novelty of objects and other adapted top-down components. To this aim, Hillaire et al [7] have studied user's gaze behavior when walking and turning in VEs. They have proposed a new model taking into account first-person navigation in order to compute an attentional weight on the whole screen based on the current rotation velocity of the camera.…”

Section: Related Workmentioning

confidence: 99%

“…The gaze behavior of users exploring VEs has been studied in [7] [18]. The top-down component of our visual attention model takes into account the observed gaze behavior resulting from the fact that users are navigating in the VE using a first-person view.…”

Section: Computation Of Statistical Screen-space Componentsmentioning

confidence: 99%

“…-Gaze behavior during camera rotations: In our model, we introduce for the first time the real-time attentional component recently proposed in [7]. In this paper, authors have studied user's gaze behavior when turning in VEs.…”

Section: Computation Of Statistical Screen-space Componentsmentioning

confidence: 99%

“…A horizontal mouse movement of 2.5cm on the table resulted in a rotation of 90 degrees of the camera in the VE (36 degrees/cm). Avatar properties were inspired by real data: height was 1.75m and walking speed was 1.15 m/s [7].…”

Section: Experimental Apparatusmentioning

confidence: 99%

“…We will show that this representation has several advantages over the mesh-based representation for visual attention models; -The use of a novel component simulating the gaze behavior of users walking and turning in VEs [7], implemented for the first time in a real-time visual attention model;…”

Section: Introductionmentioning

confidence: 99%

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Design and Application of Real-Time Visual Attention Model for the Exploration of 3D Virtual Environments

Hillaire

Lécuyer

Regia-Corte

et al. 2012

IEEE Trans. Visual. Comput. Graphics

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Abstract-This paper studies the design and application of a novel visual attention model meant to compute users gaze position automatically, i.e. without using a gaze-tracking system. The model we propose is specifically designed for real-time first-person exploration of 3D virtual environments. It is the first model adapted to this context which can compute, in real-time, a continuous gaze point position instead of a set of 3D objects potentially observed by the user. To do so, contrary to previous models which use a mesh-based representation of visual objects, we introduce a representation based on surface-elements. Our model also simulates visual reflexes and the cognitive process which takes place in the brain such as the gaze behavior associated to first-person navigation in the virtual environment. Our visual attention model combines the bottom-up and top-down components to compute a continuous gaze point position on screen that hopefully matches the user's one. We conducted an experiment to study and compare the performance of our method with a state-of-the-art approach. Our results are found significantly better with more than 100% of accuracy gained. This suggests that computing in real-time a gaze point in a 3D virtual environment is possible and is a valid approach as compared to object-based approaches. Finally, we expose different applications of our model when exploring virtual environments. We present different algorithms which can improve or adapt the visual feedback of virtual environments based on gaze information. We first propose a level-of-detail approach that heavily relies on multipletexture sampling. We show that it is possible to use the gaze information of our visual attention model to increase visual quality where the user is looking, while maintaining a high refresh rate. Second, we introduce the use of visual attention model in three visual effects inspired from the human visual system namely: depth-of-field blur, camera motions, and dynamic luminance. All these effects are computed based on simulated user's gaze, and are meant to improve user's sensations in future virtual reality applications.Index Terms-visual attention model, first person exploration, gaze tracking, visual effects, level of detail.

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Section: Related Workmentioning

confidence: 99%

Section: Computation Of Statistical Screen-space Componentsmentioning

confidence: 99%

Section: Computation Of Statistical Screen-space Componentsmentioning

confidence: 99%

Section: Experimental Apparatusmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Design and Application of Real-Time Visual Attention Model for the Exploration of 3D Virtual Environments

Hillaire

Lécuyer

Regia-Corte

et al. 2012

IEEE Trans. Visual. Comput. Graphics

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Attention Prediction in Egocentric Video Using Motion and Visual Saliency

Yamada

Sugano

Okabe

et al. 2011

Lecture Notes in Computer Science

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We propose a method of predicting human egocentric visual attention using bottom-up visual saliency and egomotion information. Computational models of visual saliency are often employed to predict human attention; however, its mechanism and effectiveness have not been fully explored in egocentric vision. The purpose of our framework is to compute attention maps from an egocentric video that can be used to infer a person's visual attention. In addition to a standard visual saliency model, two kinds of attention maps are computed based on a camera's rotation velocity and direction of movement. These rotation-based and translation-based attention maps are aggregated with a bottom-up saliency map to enhance the accuracy with which the person's gaze positions can be predicted. The efficiency of the proposed framework was examined in real environments by using a head-mounted gaze tracker, and we found that the egomotion-based attention maps contributed to accurately predicting human visual attention.

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Ultra Low Cost Eye Gaze Tracking for Virtual Environments

Swarts

Noh

2013

Virtual Augmented and Mixed Reality. Designing and Developing Augmented and Virtual Environments

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In this paper we present an ultra-low cost eye gaze tracker specifically aimed at studying visual attention in 3D virtual environments. We capture camera view and user eye gaze for each frame and project vectors back into the environment to visualize where and what subjects view over time. Additionally we show one measure of calculating the accuracy in 3D space by creating vectors from the stored data and projecting them onto a fixed sphere. The ratio of hits to non-hits provides a measure of 3D sensitivity of the setup.

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Gaze behavior and visual attention model when turning in virtual environments

Cited by 13 publications

References 13 publications

Design and Application of Real-Time Visual Attention Model for the Exploration of 3D Virtual Environments

Design and Application of Real-Time Visual Attention Model for the Exploration of 3D Virtual Environments

Attention Prediction in Egocentric Video Using Motion and Visual Saliency

Ultra Low Cost Eye Gaze Tracking for Virtual Environments

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