Wild ToFu: Improving Range and Quality of Indirect Time-of-Flight Depth with RGB Fusion in Challenging Environments
Jung H, Brasch N, Leonardis A, Navab N, Busam B (2021)
Publication Type: Conference contribution
Publication year: 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 239-248
Conference Proceedings Title: Proceedings - 2021 International Conference on 3D Vision, 3DV 2021
Event location: Virtual, Online, GBR
ISBN: 9781665426886
DOI: 10.1109/3DV53792.2021.00034
Abstract
Indirect Time-of-Flight (I-ToF) imaging is a widespread way of depth estimation for mobile devices due to its small size and affordable price. Previous works have mainly focused on quality improvement for I-ToF imaging especially curing the effect of Multi Path Interference (MPI). These investigations are typically done in specifically constrained scenarios at close distance,indoors and under little ambient light. Surprisingly little work has investigated I-ToF quality improvement in real-life scenarios where strong ambient light and far distances pose difficulties due to an extreme amount of induced shot noise and signal sparsity,caused by the attenuation with limited sensor power and light scattering. In this work,we propose a new learning based end-to-end depth prediction network which takes noisy raw I-ToF signals as well as an RGB image and fuses their latent representation based on a multi step approach involving both implicit and explicit alignment to predict a high quality long range depth map aligned to the RGB viewpoint. We test our approach on challenging real-world scenes and show more than 40% RMSE improvement on the final depth map compared to the baseline approach [33].
Involved external institutions
Germany (DE)
Canada (CA)How to cite
APA:
Jung, H., Brasch, N., Leonardis, A., Navab, N., & Busam, B. (2021). Wild ToFu: Improving Range and Quality of Indirect Time-of-Flight Depth with RGB Fusion in Challenging Environments. In Proceedings - 2021 International Conference on 3D Vision, 3DV 2021 (pp. 239-248). Virtual, Online, GBR: Institute of Electrical and Electronics Engineers Inc..
MLA:
Jung, Hyunjun, et al. "Wild ToFu: Improving Range and Quality of Indirect Time-of-Flight Depth with RGB Fusion in Challenging Environments." Proceedings of the 9th International Conference on 3D Vision, 3DV 2021, Virtual, Online, GBR Institute of Electrical and Electronics Engineers Inc., 2021. 239-248.
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