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This paper proposes a novel method to locate crowd behavior instability spatio-temporally using a velocity-field based social force model. Considering the impacts of velocity field on interaction force between individuals, we establish an improved social force model by introducing collision probability in view of velocity distribution. As compared with commonly-used social force model, which defines...
Modeling moving and deforming objects requires capturing as much information as possible during a very short time. When using off-the-shelf hardware, this often hinders the resolution and accuracy of the acquired model. Our key observation is that in as little as four frames both sparse surface-positional measurements and dense surface-orientation measurements can be acquired using a combination of...
Obtaining models of dynamic 3D objects is an important part of content generation for computer graphics. Numerous methods have been extended from static scenarios to model dynamic scenes. If the states or poses of the dynamic object repeat often during a sequence (but not necessarily periodically), we call such a repetitive motion. There are many objects, such as toys, machines, and humans, undergoing...
We consider the problem of single image object motion deblurring from a static camera. It is well-known that deblurring of moving objects using a traditional camera is ill-posed, due to the loss of high spatial frequencies in the captured blurred image. A coded exposure camera modulates the integration pattern of light by opening and closing the shutter within the exposure time using a binary code...
Modeling dynamic scenes is a challenging problem faced by applications such as digital content generation and motion analysis. Fast single-frame methods obtain sparse depth samples while multiple- frame methods often reply on the rigidity of the object to correspond a small number of consecutive shots for decoding the pattern by feature tracking. We present a novel structured-light acquisition method...
In this paper, we propose a novel method of motion segmentation through image sequence. In our work, no assumptions of boundary densities, color, or textures are made about the background or the object. Neither do we assume any special motion model to the background or the object. With the help of classic Bayesian theory, an energy function describing the piece-wise smooth motion field of the image...
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