Abstract
Phase ambiguity is a major problem in the depth measurement in either time-of-flight or phase shifting. Resolving the ambiguity using a low frequency pattern sacrifices the depth resolution, and using multiple frequencies requires a number of observations. In this paper, we propose a phase disambiguation method that combines temporal and spatial modulation so that the high depth resolution is preserved while the number of observation is kept. A key observation is that the phase ambiguities of temporal and spatial domains appear differently with respect to the depth. Using this difference, the phase can disambiguate for a wider range of interest. We develop a prototype to show the effectiveness of our method through real-world experiments.
Highlights
Depth measurement is widely used in applications such as augmented reality, factory automation, robotics, and autonomous driving
The phase ambiguity still exists in the frequency of the greatest common divisor, which requires several measurements to obtain a wider range of interest
The depths were obtained by an ordinary ToF with a single low frequency, phase shifting with single high frequency, and our method for the comparison
Summary
Depth measurement is widely used in applications such as augmented reality, factory automation, robotics, and autonomous driving. A key observation of this paper is that the phase ambiguities of the time-of-flight (ToF) and the phase shifting appear differently on the depth domain. The spatial phase is defined as the disparity domain; the depth candidates appear at gradually increasing intervals Based on this difference, the phase ambiguity can be resolved by combining temporal and spatial modulation. We combine these techniques to realize both better resolution and wider range of interest Another problem regarding the ToF is multi-path interference due to indirect light transport. Our method leverages the asymmetric relations of spatial and temporal wrapping to solve the ambiguity of the phase
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IPSJ Transactions on Computer Vision and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.