The problem of finding a next best viewpoint for 3D modeling or scene mapping has been explored in computer vision over the last decade. This paper tackles a similar problem, but with different characteristics. It proposes a method for dynamic next best viewpoint recovery of a target point while avoiding possible occlusions. Since the environment can change, the method has to iteratively find the next best view with a global understanding of the free and occupied parts. We model the problem as a set of possible viewpoints which correspond to the centers of the facets of a virtual tessellated hemisphere covering the scene. Taking into account occlusions, distances between current and future viewpoints, quality of the viewpoint and joint constraints (robot arm joint distances or limits), we evaluate the next best viewpoint. The proposal has been evaluated on 8 different scenarios with different occlusions and a short 3D video sequence to validate its dynamic performance.
Our problem includes dynamic elements in the scenario, so we have to deal with moving occlusions. @cite_2 use the information of the occluding element and assigns the next best view by maximizing the perception of the surface out of the occluded region. This solution is not applicable to our problem since our environment is dynamic so the occlusion changes over time.
@cite_2
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How to determine the camera’s next best view is a challenging problem in vision field. A next best view approach is proposed based on occlusion information in a single depth image. First, the occlu...