Abstract
The computational complexity of traditional human body recognition algorithm is higher, and the recognition effect is poor. Therefore, in this paper, an improved neural network algorithm for acceleration sensor too recognize human posture is proposed. First of all, the sliding window method is used for human posture segmentation; then, a neuron model for acceleration sensor to recognize human posture is established; finally, the pooling layer is introduced to improve the convolution neural network to prevent overfitting during recognition. Experimental results show that the proposed algorithm can improve the recognition rate and computational complexity, and has better recognition results.