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A parallel root-finding method for omnidirectional image unwrapping

机译:用于全向图像展开的并行根发现方法

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The panoramic unwrapping of catadioptric omnidirectional view (COV) sensors have mostly relied on a precomputed mapping look-up table due to an expensive computational load that generally has its bottleneck occur at solving a sextic polynomial. However, this approach causes a limitation to the viewpoint dynamics as runtime modifications to the mapping values are not allowed in the implementation. In this paper, a parallel root-finding technique using Compute Unified Device Architecture (CUDA) platform is proposed. The proposed method enables on-the-fly computation of the mapping look-up table thus facilitate in a real-time viewpoint adjustable panoramic unwrapping. Experimental results showed that the proposed implementation incurred minimum computational load, and performed at 10.3 times and 2.3 times the speed of a current generation central processing unit (CPU) respectively on a single-core and multi-core environment.
机译:由于昂贵的计算负载通常在求解Sextic多项式时,通常依赖于预先计算的映射查找表的全景展开主要依赖于预先计算的映射查找表。然而,这种方法导致对视点动态的限制作为对映射值的运行时修改不允许在实现中。在本文中,提出了一种使用计算统一设备架构(CUDA)平台的并行根发现技术。所提出的方法使映射查找表的在飞行计算中能够在实时观点方面有助于可调节的全景展开。实验结果表明,所提出的实施发生了最小的计算负荷,分别在单核和多核环境上分别在电流发电中央处理单元(CPU)的速度为10.3倍和2.3倍。

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