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Gesture Recognition Ordering System Based on Kinect v2 Stereo Vision.

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Τίτλος: Gesture Recognition Ordering System Based on Kinect v2 Stereo Vision.
Συγγραφείς: Chen, Bing-Yan, Peng, Cheng-Yu
Πηγή: Sensors & Materials; 2026, Vol. 38 Issue 4, Part 3, p2025-2051, 27p
Θεματικοί όροι: Kinect (Motion sensor), Stereo vision (Computer science), Robot control systems, Motion capture (Human mechanics), Pose estimation (Computer vision), Human-computer interaction
Περίληψη: We propose a contactless automated ordering system utilizing Kinect v2 sensing. The system applies continuous-wave indirect time-of-flight (CW-iToF) technology to detect infrared phase shifts. This sensing method generates precise 3D data by extracting 25 skeletal feature points. The system selects six key joints to formulate four three-dimensional (3D) angular features for gesture recognition. Our adaptive geometric model utilizes triangulation to calibrate interaction regions using tester height and standing distance. This sensor-driven approach achieves a recognition success rate of 96.5% at 1.5 m and 95.1% at 2.5 m. The system identifies the selected meal and instructs a robotic arm for food preparation. This architecture establishes a fully contactless and hygienic automated dining framework. [ABSTRACT FROM AUTHOR]
Copyright of Sensors & Materials is the property of MYU, Scientific Publishing Division and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Complementary Index
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  Data: Gesture Recognition Ordering System Based on Kinect v2 Stereo Vision.
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  Data: Sensors & Materials; 2026, Vol. 38 Issue 4, Part 3, p2025-2051, 27p
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  Data: <searchLink fieldCode="DE" term="%22Kinect+%28Motion+sensor%29%22">Kinect (Motion sensor)</searchLink><br /><searchLink fieldCode="DE" term="%22Stereo+vision+%28Computer+science%29%22">Stereo vision (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Robot+control+systems%22">Robot control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+capture+%28Human+mechanics%29%22">Motion capture (Human mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Pose+estimation+%28Computer+vision%29%22">Pose estimation (Computer vision)</searchLink><br /><searchLink fieldCode="DE" term="%22Human-computer+interaction%22">Human-computer interaction</searchLink>
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  Data: We propose a contactless automated ordering system utilizing Kinect v2 sensing. The system applies continuous-wave indirect time-of-flight (CW-iToF) technology to detect infrared phase shifts. This sensing method generates precise 3D data by extracting 25 skeletal feature points. The system selects six key joints to formulate four three-dimensional (3D) angular features for gesture recognition. Our adaptive geometric model utilizes triangulation to calibrate interaction regions using tester height and standing distance. This sensor-driven approach achieves a recognition success rate of 96.5% at 1.5 m and 95.1% at 2.5 m. The system identifies the selected meal and instructs a robotic arm for food preparation. This architecture establishes a fully contactless and hygienic automated dining framework. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Sensors & Materials is the property of MYU, Scientific Publishing Division and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.18494/SAM6124
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