A parallel network for the computation of structure from long-range motion

R. Laganière, F. Labrosse, P. Cohen
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Abstract

The authors propose a parallel architecture for computing the 3-D structure of a moving scene from a long image sequence, using a principle known as the incremental rigidity scheme. At each instant an internal model of the 3-D structure is updated, based upon the observations accumulated until that time. The updating process favors rigid transformations but tolerates a limited deviation from rigidity. This deviation eventually leads the internal model to converge towards the actual 3-D structure of the scene. The main advantage of this architecture is its ability to accurately estimate the 3-D structure of the scene at a low computational cost. Testing has been successfully performed on synthetic data as well as real image sequences.<>
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一种用于结构远程运动计算的并行网络
作者提出了一种并行架构,用于从长图像序列中计算运动场景的三维结构,使用称为增量刚性方案的原理。在每一个瞬间,三维结构的内部模型都会根据当时积累的观测结果进行更新。更新过程倾向于刚性转换,但允许对刚性的有限偏差。这种偏差最终导致内部模型向场景的实际三维结构收敛。该架构的主要优点是能够以较低的计算成本准确地估计场景的三维结构。测试已成功地进行了合成数据和真实图像序列。
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