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Hierarchical structure-and-motion recovery from uncalibrated images

机译:从未校准的图像进行层次结构和运动恢复

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This paper addresses the structure-and-motion problem, that requires to find camera motion and 3D structure from point matches. A new pipeline, dubbed Samantha, is presented, that departs from the prevailing sequential paradigm and embraces instead a hierarchical approach. This method has several advantages, like a provably lower computational complexity, which is necessary to achieve true scalability, and better error containment, leading to more stability and less drift. Moreover, a practical autocalibration procedure allows to process images without ancillary information. Experiments with real data assess the accuracy and the computational efficiency of the method.
机译:本文解决了结构和运动问题,该问题需要从点匹配中找到相机运动和3D结构。提出了一个新的管道,称为萨曼莎(Samantha),它偏离了当时流行的顺序范例,而采用了分层方法。此方法具有多个优点,例如可证明较低的计算复杂度(对于实现真正的可伸缩性是必需的)和更好的错误控制,从而导致更高的稳定性和更少的漂移。而且,实际的自动校准程序允许在没有辅助信息的情况下处理图像。使用真实数据进行的实验评估了该方法的准确性和计算效率。

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