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A voting strategy for visual ego-motion from stereo

机译:立体视觉视觉自我运动的投票策略

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We present a procedure for egomotion estimation from visual input of a stereo pair of video cameras. The 3D egomotion problem, which has six degrees of freedom in general, is simplified to four dimensions and further decomposed to two two-dimensional subproblems. The decomposition allows us to use a voting strategy to identify the most probable solution, avoiding the random sampling (RANSAC) or other approximation techniques. The input constitutes of image correspondences between consecutive stereo pairs, i.e. feature points do not need to be tracked over time. The experiments show that even if a trajectory is put together as a simple concatenation of frame-to-frame increments, it comes out reliable and precise.
机译:我们提出了从立体声摄像机对的视觉输入进行自我估计的程序。通常具有六个自由度的3D自我运动问题被简化为四个维度,并进一步分解为两个二维子问题。通过分解,我们可以使用投票策略来确定最可能的解决方案,而无需使用随机抽样(RANSAC)或其他近似技术。输入构成连续的立体对之间的图像对应关系,即,无需随时间跟踪特征点。实验表明,即使将轨迹作为帧到帧增量的简单连接组合在一起,它还是可靠而精确的。

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