计算机工程与应用2017，Vol.53Issue(17)：20-25,76,7.DOI:10.3778/j.issn.1002-8331.1704-0351
基于改进MLN的人类活动识别新方法
Novel approach to human activity recognition based on improved Markov logic networks
摘要
Abstract
In light of detection uncertainty in Human Activity Recognition(HAR), the calculation method of potential function in Markov Logic Networks(MLN)is improved. In the method, relational operators in first order logic are soft-ened to make the binary features extend to the interval[0, 1];the credibility of sensor event is calculated to obtain probability of corresponding ground atom. On the basis of improved MLN, a hybrid HAR framework combined ontology is proposed and corresponding algorithm is implemented. Experimental result shows that improved MLN still has high recognition accuracy in case of ADL-E dataset contained errors.关键词
检测不确定/人类活动识别/马尔可夫逻辑网络/事件可信度/活动本体Key words
detection uncertainty/human activity recognition/Markov Logic Networks(MLN)/event credibility/activity ontology分类
信息技术与安全科学引用本文复制引用
苏雷,李冠宇,田广强..基于改进MLN的人类活动识别新方法[J].计算机工程与应用,2017,53(17):20-25,76,7.基金项目
国家自然科学基金(No.61371090) （No.61371090）
国家自然科学基金青年科学基金(No.61602076). （No.61602076）
