TY - GEN
T1 - Handheld Mapping of Specular Surfaces Using Consumer-Grade Flash LiDAR
AU - Lin, Tsung Han
AU - Henley, Connor
AU - Somasundaram, Siddharth
AU - Dave, Akshat
AU - Laifenfeld, Moshe
AU - Raskar, Ramesh
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - We propose an approach to leverage multi-bounce returns of a flash LiDAR on portable smartphones for 3D specular surface reconstruction. Traditional LiDAR systems assume that all returns are one-bounce returns, which can lead to an overestimation of the true mirror surface and cause it to appear as if there is a hole. However, in reality, returns from mirror surfaces follow multi-bounce paths. We operate with a consumer-grade, coarse multi-beam flash LiDAR, enabling real-time mapping on an affordable and portable smartphone. To address the challenges posed by the coarse setup, where the transmitter and receiver are co-located, we propose solving the association problem using the 'reciprocal pair' algorithm. This algorithm can distinguish between different types of bounces from multi-bounce returns. We have demonstrated detection over multiple consecutive frames for dense mirror mapping. In addition to 3D reconstruction, we show that multi-bounce returns enhance performance in applications such as segmentation and novel view synthesis. Our method can be integrated with state-of-the-art learned-based models, enhancing their robustness in discerning ambiguous scenarios. Importantly, our approach can map various specular surfaces like mirrors and glasses without assuming specific shapes, and it can operate on non-perpendicular specular-diffuse surface pairs.
AB - We propose an approach to leverage multi-bounce returns of a flash LiDAR on portable smartphones for 3D specular surface reconstruction. Traditional LiDAR systems assume that all returns are one-bounce returns, which can lead to an overestimation of the true mirror surface and cause it to appear as if there is a hole. However, in reality, returns from mirror surfaces follow multi-bounce paths. We operate with a consumer-grade, coarse multi-beam flash LiDAR, enabling real-time mapping on an affordable and portable smartphone. To address the challenges posed by the coarse setup, where the transmitter and receiver are co-located, we propose solving the association problem using the 'reciprocal pair' algorithm. This algorithm can distinguish between different types of bounces from multi-bounce returns. We have demonstrated detection over multiple consecutive frames for dense mirror mapping. In addition to 3D reconstruction, we show that multi-bounce returns enhance performance in applications such as segmentation and novel view synthesis. Our method can be integrated with state-of-the-art learned-based models, enhancing their robustness in discerning ambiguous scenarios. Importantly, our approach can map various specular surfaces like mirrors and glasses without assuming specific shapes, and it can operate on non-perpendicular specular-diffuse surface pairs.
KW - 3D Reconstruction
KW - Multi-bounce Returns
KW - Novel View Synthesis
KW - Segmentation
KW - Specular Surfaces
UR - https://www.scopus.com/pages/publications/85203829264
U2 - 10.1109/ICCP61108.2024.10644634
DO - 10.1109/ICCP61108.2024.10644634
M3 - Conference contribution
AN - SCOPUS:85203829264
T3 - 2024 IEEE International Conference on Computational Photography, ICCP 2024 - Proceedings
BT - 2024 IEEE International Conference on Computational Photography, ICCP 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Computational Photography, ICCP 2024
Y2 - 22 July 2024 through 24 July 2024
ER -