A Benchmark for Visual SLAM Based in Infinigen

Abstract

The use of synthetic datasets for computer vision is a key factor in the improvement of many methods. Infinigen is a procedural generator of synthetic 3D scenes of the natural world with the goal of creating datasets for computer vision research. One such area of research is Visual SLAM models, which seek to map an unknown environment while simultaneously tracking an agent’s pose. I propose a Visual SLAM benchmark based on Infinigen as well as an open-source method to generate more data for SLAM algorithms using Infinigen. The Infinigen SLAM benchmark contains extremely challenging camera motion within various indoor environments. State-of-the-art Visual SLAM models perform well on the proposed benchmark, however they perform worse than on comparable SLAM benchmarks. This suggests that Infinigen is capable of producing useful data for future SLAM research.