TY - CHAP
T1 - Metrological qualification of the orbbec astra S™ Structured-Light Camera
AU - Giancola, Silvio
AU - Valenti, Matteo
AU - Sala, Remo
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer International Publishing AG, part of Springer Nature 2018.
PY - 2018
Y1 - 2018
N2 - The Orbbec Astra S™ is a promising Three-dimension (3D) camera based on the Structured-Light technology. The Chinese company released their sensor in 2015, based on a proprietary Infra-Red (IR) depth sensor. Whether it is not clear what is the physical resolution of the depth sensor, the camera can produce point cloud up to 1280 × 1024 at 5 Hz (Table 5.1). In this chapter, we limit the resolution to 640 × 480, to maintain a fair comparison with a 30 Hz frame rate. The baseline between the camera and the project is equal to 75 mm. Even though the range is limited to 2 m, the device provide a point cloud up to 2.5 m, hence we characterized it up to that range. In this chapter, we first focuses on preliminary test including the calibration of the device. Then, we provide an estimation of the random and systematic error components, in a similar fashion than previously obtained with the Kinect V2™. Last, we provide qualitative results for simple shape reconstruction. (Table presented).
AB - The Orbbec Astra S™ is a promising Three-dimension (3D) camera based on the Structured-Light technology. The Chinese company released their sensor in 2015, based on a proprietary Infra-Red (IR) depth sensor. Whether it is not clear what is the physical resolution of the depth sensor, the camera can produce point cloud up to 1280 × 1024 at 5 Hz (Table 5.1). In this chapter, we limit the resolution to 640 × 480, to maintain a fair comparison with a 30 Hz frame rate. The baseline between the camera and the project is equal to 75 mm. Even though the range is limited to 2 m, the device provide a point cloud up to 2.5 m, hence we characterized it up to that range. In this chapter, we first focuses on preliminary test including the calibration of the device. Then, we provide an estimation of the random and systematic error components, in a similar fashion than previously obtained with the Kinect V2™. Last, we provide qualitative results for simple shape reconstruction. (Table presented).
UR - http://www.scopus.com/inward/record.url?scp=85049779706&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-91761-0_5
DO - 10.1007/978-3-319-91761-0_5
M3 - Chapter
AN - SCOPUS:85049779706
T3 - SpringerBriefs in Computer Science
SP - 61
EP - 69
BT - SpringerBriefs in Computer Science
PB - Springer
ER -