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Cell-based object tracking method for 3D shape reconstruction using multi-viewpoint active cameras

机译:基于多视角主动摄像机的基于单元的3D形状重构目标跟踪方法

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3D shape of objects can provide richer information for detecting, tracking or identifying the objects than a single 2D image of them. We tackle the 3D shape and texture reconstruction of an object moving in a widespread space using multi-viewpoint active cameras. Considering 3D shape and texture reconstruction, the problem in existing tracking methods using active cameras is that they cannot calibrate the active cameras accurately. We propose a cell-based tracking method that can produce multi-viewpoint images and accurate camera parameters for every frame. Our idea is to divide the space into cells and perform active camera control and calibration based on the cells. We demonstrate the performance of our method by simulation.
机译:与对象的单个2D图像相比,对象的3D形状可以提供更丰富的信息来检测,跟踪或识别对象。我们使用多视点主动摄像机处理在广阔空间中移动的物体的3D形状和纹理重构。考虑到3D形状和纹理重建,使用主动摄像机的现有跟踪方法存在的问题是它们无法准确地校准主动摄像机。我们提出了一种基于单元格的跟踪方法,该方法可以为每个帧生成多视点图像和准确的相机参数。我们的想法是将空间划分为多个单元,并根据这些单元执行主动的摄像机控制和校准。我们通过仿真演示了我们方法的性能。

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