Orange Labs, Rennes, France.
IEEE Trans Vis Comput Graph. 2012 Mar;18(3):356-68. doi: 10.1109/TVCG.2011.154.
This paper studies the design and application of a novel visual attention model designed to compute user's 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 processes which take place in the brain such as the gaze behavior associated to first-person navigation in the virtual environment. Our visual attention model combines both 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 sometimes more than 100 percent of accuracy gained. This suggests that computing a gaze point in a 3D virtual environment in real time is possible and is a valid approach, 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 multiple-texture 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 the visual attention model in three visual effects inspired by the human visual system namely: depth-of-field blur, camera- motions, and dynamic luminance. All these effects are computed based on the simulated gaze of the user, and are meant to improve user's sensations in future virtual reality applications.
本文研究了一种新颖的视觉注意模型的设计和应用,该模型旨在自动计算用户的注视位置,即无需使用注视跟踪系统。我们提出的模型专门针对实时的第一人称 3D 虚拟环境探索而设计。它是第一个适应这种上下文的模型,可以实时计算连续的注视点位置,而不是用户可能观察到的一组 3D 对象。为此,与以前使用基于网格的视觉对象表示的模型相反,我们引入了一种基于表面元素的表示。我们的模型还模拟了视觉反射和大脑中的认知过程,例如与虚拟环境中第一人称导航相关的注视行为。我们的视觉注意模型结合了自下而上和自上而下的组件,以在屏幕上计算连续的注视点位置,希望与用户的注视点位置相匹配。我们进行了一项实验,以研究和比较我们的方法与最先进方法的性能。我们的结果发现,准确性有时提高了 100%以上,明显更好。这表明,与基于对象的方法相比,在 3D 虚拟环境中实时计算注视点是可行的,也是一种有效的方法。最后,我们展示了在探索虚拟环境时我们的模型的不同应用。我们提出了不同的算法,可以根据注视信息来改进或适应虚拟环境的视觉反馈。我们首先提出了一种严重依赖于多重纹理采样的细节层次方法。我们表明,使用我们的视觉注意模型的注视信息可以在用户注视的地方提高视觉质量,同时保持高刷新率。其次,我们引入了在三个受人类视觉系统启发的视觉效果中使用视觉注意模型的方法,即:景深模糊、相机运动和动态亮度。所有这些效果都是基于用户的模拟注视计算的,旨在提高未来虚拟现实应用中的用户感受。