Macroscopic Interferometry: Rethinking Depth Estimation with Frequency-Domain Time-of-Flight

被引：23

作者：

Kadambi, Achuta ^{[1
]}

Schiel, Jamie ^{[1
]}

Raskar, Ramesh ^{[1
]}

机构：

[1] MIT, Media Lab, Cambridge, MA 02139 USA

来源：

2016 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) | 2016年

关键词：

D O I：

10.1109/CVPR.2016.103

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A form of meter-scale, macroscopic interferometry is proposed using conventional time-of-flight (ToF) sensors. Today, ToF sensors use phase-based sampling, where the phase delay between emitted and received, high-frequency signals encodes distance. This paper examines an alternative ToF architecture, inspired by micron-scale, microscopic interferometry, that relies only on frequency sampling: we refer to our proposed macroscopic technique as Frequency-Domain Time of Flight (FD-ToF). The proposed architecture offers several benefits over existing phase ToF systems, such as robustness to phase wrapping and implicit resolution of multi-path interference, all while capturing the same number of subframes. A prototype camera is constructed to demonstrate macroscopic interferometry at meter scale.

引用

页码：893 / 902

页数：10