Practical Coding Function Design for Time-Of-Flight Imaging

Felipe Gutierrez-Barragan, Syed Azer Reza, Andreas Velten, Mohit Gupta; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 1566-1574

Abstract


The depth resolution of a continuous-wave time-of-flight (CW-ToF) imaging system is determined by its coding functions. Recently, there has been growing interest in the design of new high-performance CW-ToF coding functions. However, these functions are typically designed in a hardware agnostic manner, i.e., without considering the practical device limitations, such as bandwidth, source power, digital (binary) function generation. Therefore, despite theoretical improvements, practical implementation of these functions remains a challenge. We present a constrained optimization approach for designing practical coding functions that adhere to hardware constraints. The optimization problem is non-convex with a large search space and no known globally optimal solutions. To make the problem tractable, we design an iterative, alternating least-squares algorithm, along with convex relaxation of the constraints. Using this approach, we design high-performance coding functions that can be implemented on existing hardware with minimal modifications. We demonstrate the performance benefits of the resulting functions via extensive simulations and a hardware prototype.

Related Material


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[bibtex]
@InProceedings{Gutierrez-Barragan_2019_CVPR,
author = {Gutierrez-Barragan, Felipe and Reza, Syed Azer and Velten, Andreas and Gupta, Mohit},
title = {Practical Coding Function Design for Time-Of-Flight Imaging},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}