ترجمه مقاله نقش ضروری ارتباطات 6G با چشم انداز صنعت 4.0
- مبلغ: ۸۶,۰۰۰ تومان
ترجمه مقاله پایداری توسعه شهری، تعدیل ساختار صنعتی و کارایی کاربری زمین
- مبلغ: ۹۱,۰۰۰ تومان
Abstract
In this paper, a novel action recognition method is proposed based on hierarchical dynamic Bayesian network (HDBN). The algorithm is divided into system learning stage and action recognition stage. In the stage of system learning, the video features are extracted using deep neural networks firstly, and using hierarchical clustering and assisting manually, a hierarchical action semantic dictionary (HASD) is built. The next, we construct the HDBN graph model to present video sequence. In the stage of recognition, we first get the representative frames of unknown video using deep neural networks. The features are inputted into the HDBN, and the HDBN inference is used to get recognition results. The testing results show the proposed method is promising.
5 Conclusions
In this paper, a novel the HDBN-based action recognition method is proposed. Our contribution can be described as:
(1) We propose a novel graph-based action recognition model. The model combines the hierarchical action semantic dictionary and Bayesian graph model inference together, and uses recursion-based method to recognize action video data.
(2) Based on some theories, such as Bayesian rules, graph model, the probability-based recursion calculation structure is presented to obtain the higher accuracy of action recognition. Experimental results show that the proposed model has better performance than some existing algorithms.