A parallel root-finding method for omnidirectional image unwrapping

Abstract

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.