Single-shot spatial frequency multiplex fringe pattern for phase unwrapping using deep learning

Author(s):  
Yixuan Li ◽  
Jiaming Qian ◽  
Shijie Feng ◽  
Qian Chen ◽  
Chao Zuo
2021 ◽  
Author(s):  
Jiaming Qian ◽  
Shejie Feng ◽  
Yixuan Li ◽  
Qian Chen ◽  
Chao Zuo

APL Photonics ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 046105 ◽  
Author(s):  
Jiaming Qian ◽  
Shijie Feng ◽  
Tianyang Tao ◽  
Yan Hu ◽  
Yixuan Li ◽  
...  

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1718
Author(s):  
Chien-Hsing Chou ◽  
Yu-Sheng Su ◽  
Che-Ju Hsu ◽  
Kong-Chang Lee ◽  
Ping-Hsuan Han

In this study, we designed a four-dimensional (4D) audiovisual entertainment system called Sense. This system comprises a scene recognition system and hardware modules that provide haptic sensations for users when they watch movies and animations at home. In the scene recognition system, we used Google Cloud Vision to detect common scene elements in a video, such as fire, explosions, wind, and rain, and further determine whether the scene depicts hot weather, rain, or snow. Additionally, for animated videos, we applied deep learning with a single shot multibox detector to detect whether the animated video contained scenes of fire-related objects. The hardware module was designed to provide six types of haptic sensations set as line-symmetry to provide a better user experience. After the system considers the results of object detection via the scene recognition system, the system generates corresponding haptic sensations. The system integrates deep learning, auditory signals, and haptic sensations to provide an enhanced viewing experience.


Author(s):  
Hongyu Zhou ◽  
Chuanli Cheng ◽  
Hao Peng ◽  
Dong Liang ◽  
Xin Liu ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Parsa Omidi ◽  
Mohamadreza Najiminaini ◽  
Mamadou Diop ◽  
Jeffrey J. L. Carson

AbstractSpatial resolution in three-dimensional fringe projection profilometry is determined in large part by the number and spacing of fringes projected onto an object. Due to the intensity-based nature of fringe projection profilometry, fringe patterns must be generated in succession, which is time-consuming. As a result, the surface features of highly dynamic objects are difficult to measure. Here, we introduce multispectral fringe projection profilometry, a novel method that utilizes multispectral illumination to project a multispectral fringe pattern onto an object combined with a multispectral camera to detect the deformation of the fringe patterns due to the object. The multispectral camera enables the detection of 8 unique monochrome fringe patterns representing 4 distinct directions in a single snapshot. Furthermore, for each direction, the camera detects two π-phase shifted fringe patterns. Each pair of fringe patterns can be differenced to generate a differential fringe pattern that corrects for illumination offsets and mitigates the effects of glare from highly reflective surfaces. The new multispectral method solves many practical problems related to conventional fringe projection profilometry and doubles the effective spatial resolution. The method is suitable for high-quality fast 3D profilometry at video frame rates.


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