What Are Optimal Coding Functions for Time-of-Flight Imaging?
Abstract
The depth resolution achieved by a continuous wave time-of-flight (C-ToF) imaging system is determined by the coding (modulation and demodulation) functions that it uses. Almost all current C-ToF systems use sinusoid or square coding functions, resulting in a limited depth resolution. In this article, we present a mathematical framework for exploring and characterizing the space of C-ToF coding functions in a geometrically intuitive space. Using this framework, we design families of novel coding functions that are based on Hamiltonian cycles on hypercube graphs. Given a fixed total source power and acquisition time, the new Hamiltonian coding scheme can achieve up to an order of magnitude higher resolution as compared to the current state-of-the-art methods, especially in low signal-to-noise ratio (SNR) settings. We also develop a comprehensive physically-motivated simulator for C-ToF cameras that can be used to evaluate various coding schemes prior to a real hardware implementation. Since most off-the-shelf C-ToF sensors use sinusoid or square functions, we develop a hardware prototype that can implement a wide range of coding functions. Using this prototype and our software simulator, we demonstrate the performance advantages of the proposed Hamiltonian coding functions in a wide range of imaging settings.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Feb 28, 2018
- Source ID
- 10.1145/3152155
Entities
People
- Andreas Velten
- Eric Breitbach
- Mohit Gupta
- Shree K. Nayar
Organizations
- Columbia University
- Defense Advanced Research Projects Agency
- Office of Naval Research
- University of Wisconsin–Madison