Aiming at the problem of low dynamic gesture recognition accuracy in complex environment, a dynamic gesture recognition technique in complex environment based on attention mechanism convolutional neural network is proposed. First of all, the long short term memory network is adopted to learn the weight of each filter, and predict human appearance correlated filter banks; then, the convolutional neural network is used to extract the trajectory images, and construct a color trajectory image; finally, trajectory images are delivered to attention convolutional neural network to train, the trained neural network is taken advantage to recognize the target gesture in complex environment. Experimental results indicate that the proposed gesture recognition algorithm can detect and track the dynamic gestures, at the same time, it realizes a good gesture recognition accuracy.