Artificial immune system optimization based duplex kinect skeleton fusion

Gündüz, Ali Fatih; Şen, Mehmed Oğuz; Karcı, Ali; Yeroğlu, Celaleddin

doi:10.1109/idap.2017.8090248

Cited by 1 publication

(1 citation statement)

References 16 publications

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“…Numerous papers focusing on the skeleton tracking capabilities of Kinect v1 and Kinect v2 have been published [17][18][19][20][21][22][23]. New ideas making use of the new Azure Kinect have already been published.…”

Section: Introductionmentioning

confidence: 99%

Skeleton Tracking Accuracy and Precision Evaluation of Kinect V1, Kinect V2, and the Azure Kinect

Tölgyessy¹,

Dekan²,

Chovanec³

2021

Applied Sciences

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The Azure Kinect, the successor of Kinect v1 and Kinect v2, is a depth sensor. In this paper we evaluate the skeleton tracking abilities of the new sensor, namely accuracy and precision (repeatability). Firstly, we state the technical features of all three sensors, since we want to put the new Azure Kinect in the context of its previous versions. Then, we present the experimental results of general accuracy and precision obtained by measuring a plate mounted to a robotic manipulator end effector which was moved along the depth axis of each sensor and compare them. In the second experiment, we mounted a human-sized figurine to the end effector and placed it in the same positions as the test plate. Positions were located 400 mm from each other. In each position, we measured relative accuracy and precision (repeatability) of the detected figurine body joints. We compared the results and concluded that the Azure Kinect surpasses its discontinued predecessors, both in accuracy and precision. It is a suitable sensor for human–robot interaction, body-motion analysis, and other gesture-based applications. Our analysis serves as a pilot study for future HMI (human–machine interaction) designs and applications using the new Kinect Azure and puts it in the context of its successful predecessors.

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