Five-point algorithm: An efficient cloud-based FPGA implementation

The 5-point relative pose problem is to identify the possible relative camera motions given five matching points from two calibrated views. Several algorithms for solving this problem have been presented in the literature providing different tradeoffs in terms of computational complexity and accuracy of the results. Indeed, the research in this field is driven mostly by the need for accurate solutions and high performance to cope with real-time requirements. In this work we propose an implementation to solve the 5-point relative pose problem accelerated on Field Programmable Gate Array (FPGA). The proposed architecture implements the classical Nister's algorithm as a deep pipeline deployed on a AWS F1 instance and outperforms software implementations by a factor ranging from 7.2X to 233X. Furthermore, it achieves a speedup of 64.2X compared to the Nister's software implementation with comparable accuracy.