针对隐条件随机场(HCRF)的实时性问题和隐动态条件随机场(LDCRF)行为转换时的标记偏差问题,提出了一种基于分层分数条件随机场(SFCRF)模型的行为识别算法.该算法改进了LDCRF,并提出分数标记的概念,将人体行为的完整性和有向性具体化.实验结果表明,该算法取得了比条件随机场(CRF)、HCRF和LDCRF更好的识别效果.%In view of real-time issue of the Hidden Conditional Random Field (HCRF) and marked deviation problem of the Latent-Dynamic Conditional Random Field (LDCRF) during behavior transforming, this article proposed a kind of behavior recognition algorithm based on Stratified Fractal Conditional Random Field ( SFCRF). The proposed algorithm improved LDCRF and put forward the concept of score mark, which made the integrity and direction of human behavior specific. The experimental results show that the proposed algorithm can obtain better recognition effect than Conditional Random Field (CRF), HCRF and LDCRF.
展开▼
