Identifying the confidence level of activity recognition via HMM - Chang-hai WANG; Jian-zhong ZHANG; Jing-dong XU; Yu-wei XU (Tongxin xuebao)
A context-based method to identify the confidence level of activ recognition was proposed,referred to as S-HMM(sliding window hidden Markov model),which reduced the confusion rate and facilitated the transfer learning.With S-HMM,the activity recognition sequence was modeled as HMM(hidden Markov model)and the corresponding probability was adopted as the confidence level.This ,S-HMM removed the dependency of the confidence level on the sample distribution in the feature space.S-HMM is extensively evaluated based on real-life activity data,demonstrat-ing a reduced confusion rate of 37% when compared to the state-of-the-art methods.