Lock-in Time-of-Flight (ToF) Cameras: A Survey

By Sergi Foix, Guillem Alenyà, Carme Torras. IEEE Sensors Journal, 2011

658 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Environmental Engineering, Instrumentation

View Paper: https://www.semanticscholar.org/paper/24c68190ac07111547f2a422d3cdcee9cfec041e

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. K. Müller
2. Liliana Lo Presti
3. Marco La Cascia
4. Jiri Matas
5. Adrien Bartoli
6. Radu Patrice Horaud
7. Lena Maier-Hein
8. Andreas Kolb

In Environmental Engineering

1. K. Müller
2. Jiri Matas
3. Radu Patrice Horaud
4. Miles E. Hansard
5. Clément Ménier

In Instrumentation

1. Radu Patrice Horaud
2. Miles E. Hansard
3. Clément Ménier

Citations in the corpus

• An overview of depth cameras and range scanners based on time-of-flight technologies (2016, methodology): “A quantitative analysis of these sources of errors is available in [18].”
• The status, challenges, and future of additive manufacturing in engineering (2015, neutral): “Numerous techniques have been developed including photogrammetry [291], stereovision [292], light field [293], shape from shading [294], time of flight [295], structured light [296], and digital fringe projection [297].”
• Overview of the Multiview and 3D Extensions of High Efficiency Video Coding (2016, background): “They could also be acquired by a special depth camera; this particular area has seen notable advances in recent years with designs based on structured light [5] or timeof-flight based imaging [6].”
• 3D skeleton-based human action classification: A survey (2016, background): “The estimated distance can be unreliable in case of low spatial resolution, as well as because of errors caused by radiometric, geometric and illumination variations, motion blur, background light, and multiple re fl ections [78].”
• Evaluating and Improving the Depth Accuracy of Kinect for Windows v2 (2015, methodology): “Typical devices include Cyberware laser head scanner [3], MESA Imaging SRFamily Time-of-Flight (ToF) camera [4], and PrimeSense Carmine structured-light cameras [5].”
• T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-Less Objects (2017, background): “According to Foix et al. [16], a 3-degree polynomial function suffices to correct depth in the 1 – 2 m range.”
• Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery (2013, background): “(Foix et al., 2011), the main reason for this effect is still the subject of investigation.”