摘要
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.
出处
《计算机应用》
CSCD
北大核心
2013年第4期957-959,997,共4页
journal of Computer Applications
基金
国家863计划项目(2008AA01Z148)
国家自然科学基金资助项目(60975022)
博士点专项科研基金资助项目(20102304110004)
关键词
隐条件随机场
隐动态条件随机场
标记偏差
行为识别
条件随机场
Hidden Conditional Random Field（HCRF）
Latent-Dynamic Conditional Random Field（LDCRF）
marked deviation
behavior recognition
Conditional Random Field（CRF）
