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We present a min-cut based method of segmenting objects in point clouds. Given an object location, our method builds a k-nearest neighbors graph, assumes a background prior, adds hard foreground (and optionally background) constraints, and finds the min-cut to compute a foreground-background segmentation. Our method can be run fully automatically, or interactively with a user interface. We test our...
Here, we address the problem of tracking of polyhedral objects in images from traffic scene. The matching of the model is achieved by minimizing the distance between the projected segments of the 3D model and the segments extracted in the 2D image. The success depends on the global optimization of the cost function that quantifies the quality of alignment. The existence of numerous local minima makes...
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