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Computational perception of scene dynamics

机译:现场动态的计算感知

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Understanding observations of interacting objects requires one to reason about qualitative scene dynamics. Forexample, on observing a hand lifting a can, we may infer that an 'active' hand is applying an upwards force (by grasping) to lift a 'passive' can. We present an implemented computational theory that derives such dynmaic descriptions directly from camera input. Our approach is based on an analysis of the Newtonian mechanics of a simplified scene model. Interpretations are expressed in terms of assertions about the kinematic and dynamic properties of the scene. The feasibility of interpretations can be determined relative ato Netwonian mechanics by a reduction to linear programming. Finally, to select plausible interpretations, multiple feasible solutions are compared using a preference hierarchy. We provide computational examples to demonstrate that our model is sufficiently rich to describe a wide variety of image sequences.
机译:理解互动对象的观察需要一个地推理定性场景动态。 对于观察手升起的手,我们可以推断一个“活跃”的手正在施加向上力(通过抓握)来提升“被动”。 我们提出了一种实现的计算理论,其直接从相机输入导出这种Dynmaic描述。 我们的方法是基于对简化场景模型的牛顿力学的分析。 以关于场景的运动和动态属性的断言表示的解释。 解释的可行性可以通过减少到线性编程来确定相对的ATO Netwonian力学。 最后,为了选择合理的解释,使用偏好层次结构进行比较多种可行的解决方案。 我们提供计算示例,以证明我们的模型足够丰富,以描述各种各样的图像序列。

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