Abstract
Over the past 10 years, we have seen a democratization of range sensing technology. While previously range sensors have been highly expensive and only accessible to a few domain experts, such sensors are nowadays ubiquitous and can even be found in the latest generation of mobile devices, e.g., current smartphones. This democratization of range sensing technology was started with the release of the Microsoft Kinect, and since then many different commodity range sensors followed its lead, such as the Primesense Carmine, Asus Xtion Pro, and the Structure Sensor from Occipital. The availability of cheap range sensing technology led to a big leap in research, especially in the context of more powerful static and dynamic reconstruction techniques, starting from 3D scanning applications, such as KinectFusion, to highly accurate face and body tracking approaches. In this chapter, we have a detailed look into the different types of existing range sensors. We discuss the two fundamental types of commodity range sensing techniques in detail, namely passive and active sensing, and we explore the principles these technologies are based on. Our focus is on modern active commodity range sensors based on time of flight and structured light. We conclude by discussing the noise characteristics, working ranges, and types of errors made by the different sensing modalities.
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Zollhöfer, M. (2019). Commodity RGB-D Sensors: Data Acquisition. In: Rosin, P., Lai, YK., Shao, L., Liu, Y. (eds) RGB-D Image Analysis and Processing. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-030-28603-3_1
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