Abstract: In traditional methods for capturing human upper limb movements, sensor data is susceptible to noise interference and occlusion, resulting in data loss and affecting the accuracy of motion capture. Therefore, the cuckoo search algorithm is introduced, which utilizes its global search ability to find the optimal or approximately optimal solution in the presence of noise and occlusion, thereby improving the robustness of data processing and achieving accurate capture of human upper limb movements. Firstly, the Kinect sensor is used to collect data on human upper limb movements, and the quaternion method is used to obtain the position coordinates of human upper limb joint points. Then, based on optimization algorithms, the orientation of human upper limb movements is determined. Finally, the cuckoo search algorithm is used to optimize the results of human upper limb motion capture, improving the accuracy of joint point positioning. The coordinates of the upper limb joint points measured by the optimized sensor are connected to determine the position of the upper limb, and combined with the orientation of the upper limb, upper limb motion capture is achieved. The experimental results show that the method has high accuracy in measuring the orientation angle of the upper limbs and good motion capture performance.

Key words: cuckoo search algorithm, human upper limb motion capture, Kinect sensor, quaternion method, optimization algorithm