Design of Human Posture Recognition System Integrating Computer Vision and Deep Learning Algorithm
Jinquan Chu, Haoyi Wang, Anxing Dong, Yuming Chen · 2023
In this article, a human posture recognition model combining computer vision and deep learning (DL) algorithm is proposed. Under the condition of keeping the data structure and sample labels unchanged, the model randomly cuts the video frame images by using the horizontal translation matrix, which effectively expands the data set samples, thus reducing the risk of over-fitting of the model to some extent. The experimental results show that the improved human target detection algorithm in this article can effectively improve the detection performance of the algorithm, and the computational complexity of the human posture recognition algorithm is small, which increases the correlation between adjacent video frames in the recognition process, and improves the accuracy of posture recognition while ensuring real-time. The realization of this algorithm is of great significance for building a simplified human posture recognition system with high response and accuracy.