Gesture Recognition Ordering System Based on Kinect v2 Stereo Vision

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.