Sometimes, it is difficult to buy objects in the sense of there not evident adaptation to the anticipated place. To facilitate this operation, it would be possible to study virtually the disposition without being obli...
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We propose an adapted shape-matching approach for the efficient and robust simulation of clothing. A combination of two different cluster types is employed to account for high stretching and shearing, and low bending ...
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This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the...
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This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the variation of flow in different time periods and intersections is studied. According to the long-range correlation in different time scales, it mainly discuss the effect of intersection location in road net, people activity customs and special traffic controls on urban traffic flow. As demonstrated by obtained results, the urban traffic flow represents three-phase characters similar to highway traffic. Moreover, compared by the two groups of data obtained before and after the special traffic restrictions (vehicles with special numbered plates only run in a special workday) enforcement, it indicates that the rules not only reduce the flow but also avoid irregular fluctuation.
We propose a notion of affordance that takes into account physical quantities generated when the human body interacts with real-world objects, and introduce a learning framework that incorporates the concept of human ...
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Frame-to-frame coherence is the highly structured relationship that exists between successive frames of certain animation sequences. From the point of view of the hidden surface computation, this implies that parts of...
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Current state-of-the-art object classification systems are trained using large amounts of hand-labeled images. In this paper, we present an approach that shows how to use unlabeled video sequences, comprising weakly-r...
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Amongst all atmospheric phenomena, rain is probably the most commonly used effect to create realistic immersive virtual environments, and to set the mood in movie storytelling. Although not immediately obvious, the be...
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ISBN:
(纸本)9781450379281
Amongst all atmospheric phenomena, rain is probably the most commonly used effect to create realistic immersive virtual environments, and to set the mood in movie storytelling. Although not immediately obvious, the beauty of rain emanates from the interplay of the involved light-matter interaction, generating effects of refraction and reflection, coupled with scattering effects. At the core, rain consists of water droplets under the influence of gravity. Current state of the art methods of generating rain are either computationally burdening, or not realistic enough. The key idea we introduce in this paper is to consider these droplets as transparent objects in the environment matting (EM) framework. This enables careful preprocessing to discover the light transport phenomena. We end up with a free-viewpoint real-time technique of simulating realistic droplets and rain in novel environments.
Head pose estimation is an important step in many face related applications. In this paper, we propose to use random regression forests to estimate head poses in 2D face images. Given a 2D face image, Gabor filters ar...
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We propose a notion of affordance that takes into account physical quantities generated when the human body interacts with real-world objects, and introduce a learning framework that incorporates the concept of human ...
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ISBN:
(纸本)9781467388511
We propose a notion of affordance that takes into account physical quantities generated when the human body interacts with real-world objects, and introduce a learning framework that incorporates the concept of human utilities, which in our opinion provides a deeper and finer-grained account not only of object affordance but also of people's interaction with objects. Rather than defining affordance in terms of the geometric compatibility between body poses and 3D objects, we devise algorithms that employ physicsbased simulation to infer the relevant forces/pressures acting on body parts. By observing the choices people make in videos (particularly in selecting a chair in which to sit) our system learns the comfort intervals of the forces exerted on body parts (while sitting). We account for people's preferences in terms of human utilities, which transcend comfort intervals to account also for meaningful tasks within scenes and spatiotemporal constraints in motion planning, such as for the purposes of robot task planning.
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