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A robust technique for structure from planar motion using image sequences

机译:使用图像序列从平面运动构造结构的可靠技术

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This paper proposes a robust method for recovery of motion and structure from two image sequences taken by stereo cameras undergoing a planar motion. The feature correspondence between images are extracted and refined automatically by the relation of the stereo cameras and the property of the motion. To improve the robustness, the random sample consensus (RANSAC) algorithm is adopted in the motion and structure estimation. Unlike other researchers to recover of epipolar geometry, here we use it to recover the 2D motion and to exclude the outliers not only out of the epipolar lines but also in them. Also the spirit of RANSAC is used in structure estimation to exclude the outlier from the sequence view. The most important contribution of this work is a way to make this estimation scheme more robust and efficient so as to be used in real applications. The experiments indoor and outdoor have been done to verify the feasibility of the algorithm. The results show the algorithm is robust and efficient for applications in planar motion.
机译:本文提出了一种稳健的方法,用于从经历平面运动的立体声相机拍摄的两个图像序列恢复运动和结构。通过立体相机的关系和运动的属性,自动提取图像之间的特征对应。为了提高稳健性,在运动和结构估计中采用随机样本共识(RANSAC)算法。与其他研究人员不同,在这里,我们使用它来恢复2D运动并排除异常值,不仅从骨头线路中排出,而且还在其中排除异常值。此外,RANSAC的精神用于结构估计,以排除序列视图中的异常值。这项工作最重要的贡献是使该估算方案更加强大和有效的方法,以便在真实应用中使用。已经进行了室内和室外的实验以验证算法的可行性。结果表明,该算法对于平面运动中的应用是强大而有效的。

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