TY - GEN
T1 - A comparison and analysis of RGB-D cameras' depth performance for robotics application
AU - Jing, Changjuan
AU - Potgieter, Johan
AU - Noble, Frazer
AU - Wang, Ruili
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/14
Y1 - 2017/12/14
N2 - Consumer-grade RGB-D cameras capture RGB images along with per-pixel depth information, and because of their limited cost and ability to measure distances at a high frame rate, have been used in robotics and computer vision application. However, drawbacks include the repeatability and accuracy of RGB-D cameras for object detection and localization. This paper investigates and compares RGB-D cameras' performance in terms of depth image quality, depth clouds distribution, etc. performance and configuration methods of frequently used cameras, e.g. PrimeSense, Kinect V1 and Kinect V2, in order to provide useful advice when choosing a camera for robotic applications. Experimental and Point Cloud Library (PCL)-based methods are introduced for point-to-plane distance detection. Based on the obtained results, a relationship between measurements and ground truth is built.
AB - Consumer-grade RGB-D cameras capture RGB images along with per-pixel depth information, and because of their limited cost and ability to measure distances at a high frame rate, have been used in robotics and computer vision application. However, drawbacks include the repeatability and accuracy of RGB-D cameras for object detection and localization. This paper investigates and compares RGB-D cameras' performance in terms of depth image quality, depth clouds distribution, etc. performance and configuration methods of frequently used cameras, e.g. PrimeSense, Kinect V1 and Kinect V2, in order to provide useful advice when choosing a camera for robotic applications. Experimental and Point Cloud Library (PCL)-based methods are introduced for point-to-plane distance detection. Based on the obtained results, a relationship between measurements and ground truth is built.
UR - http://www.scopus.com/inward/record.url?scp=85048473353&partnerID=8YFLogxK
U2 - 10.1109/M2VIP.2017.8211432
DO - 10.1109/M2VIP.2017.8211432
M3 - Conference contribution
AN - SCOPUS:85048473353
T3 - 2017 24th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2017
SP - 1
EP - 6
BT - 2017 24th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2017
Y2 - 21 November 2017 through 23 November 2017
ER -