GestureStudy: Mouse Gesture Recognition Algorithm and Experimental Program Based on Backpropagation Neural Network

This paper presents a mouse gesture recognition algorithm and experimental program called GestureStudy, which utilizes a Backpropagation (BP) neural network architecture. The algorithm achieves accurate mouse gesture recognition through supervised training of multilayer perceptrons with gradient descent optimization. Key implementation components include gesture trajectory preprocessing, feature extraction modules, and neural network classification layers. This approach demonstrates applicability across various domains including human-computer interaction systems and virtual reality interfaces. The experimental program validates the algorithm's effectiveness through precision/recall metrics and real-time performance testing. The research contributes novel methodology and implementation frameworks for advancing mouse gesture recognition technology, with particular emphasis on robust neural network training techniques and real-world deployment considerations.