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Towards real-time camera egomotion estimation and three-dimensional scene acquisition from monocular image streams

机译:从单眼图像流走向实时相机自我估计和三维场景采集

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The three-dimensional reconstruction of rigid scenes from monocular image streams is based on the former calculation of the relative camera pose between at least two successive image frames. This egomotion estimation has not been solved satisfactorily by relying only on corresponding image features, such as points or lines, due to noise, critical motion patterns or special point configurations. This paper describes a framework for incorporating inertial measurements from gyroscopes, accelerometers and magnetometers to achieve an improved performance of the estimation of camera motion and scene structure in terms of accuracy, robustness and computational costs. The framework is designed as a dual-track system containing a visual and a inertial route.
机译:从单眼图像流对刚性场景进行三维重建是基于对至少两个连续图像帧之间的相对相机姿态的先前计算。由于噪声,临界运动模式或特殊点配置,仅依靠相应的图像特征(例如点或线)不能令人满意地解决这种自我运动估计。本文介绍了一个框架,该框架结合了陀螺仪,加速计和磁力计的惯性测量,从而在准确性,鲁棒性和计算成本方面实现了对摄像机运动和场景结构的估计的改进性能。该框架设计为包含视觉和惯性路线的双轨系统。

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