Dense urban scene reconstruction using stereo depth image triangulation

Jonas Haeling; Marc Necker; Andreas Schilling

doi:10.1117/12.2556688

31 January 2020 Dense urban scene reconstruction using stereo depth image triangulation

Jonas Haeling, Marc Necker, Andreas Schilling

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114331R (2020) https://doi.org/10.1117/12.2556688
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

In this paper, we present a novel 3D scene reconstruction framework from a single front-mounted stereo camera on a moving vehicle. We propose image triangulations to efficiently render a 3D scene only from 2D textures, while introducing tube meshes as an effective way to render out-of-frustum points. Furthermore, we derive a 3D extended Kalman filter to fuse stereo estimates temporally between frames and showcase a render pipeline, which exploits OpenGL shaders to offload computational costs from the CPU to the GPU. Our approach is able to increase the stereo accuracy compared to competing approaches on the KITTI visual odometry dataset. We also introduce a challenging view prediction evaluation scenario on the SYNTHIA dataset, in which our approach comes out on top in terms of SSIM, 1-NCC error and completeness.

Citation Download Citation

Jonas Haeling, Marc Necker, and Andreas Schilling "Dense urban scene reconstruction using stereo depth image triangulation", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114331R (31 January 2020); https://doi.org/10.1117/12.2556688

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