Automatic real-time generalized phase-shifting interferometry to process interferograms with spatio-temporal visibility

2013 ◽  
Author(s):  
Rigoberto Juarez-Salazar ◽  
Carlos Robledo-Sanchez ◽  
Cruz Meneses-Fabian ◽  
Gustavo Rodriguez-Zurita ◽  
Fermin Guerrero Sanchez ◽  
...  
Keyword(s):  
Real Time ◽  
Phase Shifting ◽  
Phase Shifting Interferometry ◽  
Spatio Temporal

Noise reduction by spatio-temporal filtering on parallel phase-shifting interferometry

2020 ◽  
Author(s):  
Nachanant Chitanont ◽  
Pannarong Thongtangsai ◽  
Dabasvee Tachatanachai ◽  
Praewa Chatsuksiridech ◽  
Fumihiko Imaeda ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Phase Shifting ◽  
Temporal Filtering ◽  
Phase Shifting Interferometry ◽  
Spatio Temporal

Image Based MEMS Dynamics Characterization System

2004 ◽  
Author(s):  
Jinpeng Bai ◽  
Yongjun Xie ◽  
Tielin Shi ◽  
Sheng Liu
Keyword(s):  
Real Time ◽  
Nonlinear Behavior ◽  
Phase Shifting ◽  
Mems Devices ◽  
Dynamic Behaviors ◽  
Phase Shifting Interferometry ◽  
Time Observation ◽  
Real Time Observation

For MEMS with moveable parts, it is crucial for the designers and fabricators to conduct real time observation of dynamic behaviors of the device and the packaged system, especially when the nonlinear behavior is obvious. This article presents an image based characterization system in which phase shifting interferometry, microvision, and strobe illumination are integrated. Several measurement examples of MEMS devices carried out by this system are presented.

Passthrough+

2020 ◽  
Vol 3 (1) ◽  
pp. 1-17
Author(s):  
Gaurav Chaurasia ◽  
Arthur Nieuwoudt ◽  
Alexandru-Eugen Ichim ◽  
Richard Szeliski ◽  
Alexander Sorkine-Hornung
Keyword(s):  
Real Time ◽  
Video Encoding ◽  
View Synthesis ◽  
Performance Constraints ◽  
Trade Offs ◽  
Stereoscopic View ◽  
Target User ◽  
Spatio Temporal ◽  
And Performance ◽  
3D Scene

We present an end-to-end system for real-time environment capture, 3D reconstruction, and stereoscopic view synthesis on a mobile VR headset. Our solution allows the user to use the cameras on their VR headset as their eyes to see and interact with the real world while still wearing their headset, a feature often referred to as Passthrough. The central challenge when building such a system is the choice and implementation of algorithms under the strict compute, power, and performance constraints imposed by the target user experience and mobile platform. A key contribution of this paper is a complete description of a corresponding system that performs temporally stable passthrough rendering at 72 Hz with only 200 mW power consumption on a mobile Snapdragon 835 platform. Our algorithmic contributions for enabling this performance include the computation of a coarse 3D scene proxy on the embedded video encoding hardware, followed by a depth densification and filtering step, and finally stereoscopic texturing and spatio-temporal up-sampling. We provide a detailed discussion and evaluation of the challenges we encountered, as well as algorithm and performance trade-offs in terms of compute and resulting passthrough quality.;AB@The described system is available to users as the Passthrough+ feature on Oculus Quest. We believe that by publishing the underlying system and methods, we provide valuable insights to the community on how to design and implement real-time environment sensing and rendering on heavily resource constrained hardware.

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