Fringe projection techniques: Whither we are?

By S. S. Gorthi, P. Rastogi. 2010

1,281 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Geology, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/f1f5b603dd34ec26939517348d77df10992798f0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Guohua Gu
2. Chao Zuo
3. Li Rubin
4. Guochen Shen
5. Fangxiaoyu Feng
6. Shijie Feng
7. Jason Geng
8. Qian Chen

In Geology

1. Chao Zuo
2. Jason Geng
3. Qian Chen

In Mechanical Engineering

1. Chao Zuo
2. Shijie Feng
3. Jason Geng
4. Qian Chen

Citations in the corpus

• High-speed three-dimensional shape measurement for dynamic scenes using bi-frequency tripolar pulse-width-modulation fringe projection (2013, positive): “Fringe projection methods have been considered one of the most reliable techniques for recovering the shape of objects because of their accuracy and efficiency [2].”
• In situ surface topography of laser powder bed fusion using fringe projection (2016, background): “Fringe projection is a viable solution, being well suited to measure an areal profile of a mid-sized object [8].”
• Structured-light 3D surface imaging: a tutorial (2011, background): “The gray code determines absolute range of phase without any ambiguity, while the phase shift offers subpixel resolution beyond the number of stripes provided by the gray code [10,12].”