基于HMM的动作识别结果可信度计算方法

doi:10.11959/j.issn.1000-436x.2016102

Abstract

Abstract:

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.

Key words: activity recognition, hidden Markov model, confusion rate, confidence level

Chang-hai WANG,Jian-zhong ZHANG,Jing-dong XU,Yu-wei XU. Identifying the confidence level of activity recognition via HMM[J]. Journal on Communications, 2016, 37(5): 143-151.

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References 22

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位置	跑步	上楼	下楼	静止	走路
位置1	94	87	86	87	96
位置4	82	79	81	78	85
位置5	88	88	83	71	78
位置6	97	86	82	88	77
总计	361	340	332	324	336

动作	跑步	上楼	下楼	静止	走路
跑步	52	0	0	0	3
上楼	0	54	0	1	3
下楼	0	0	44	0	6
静止	0	1	1	71	3
走路	3	3	5	5	101
总计	55	58	50	77	116

动作	跑步	上楼	下楼	静止	走路
跑步	0.947	0.023	0.021	0.000	0.010
上楼	0.010	0.800	0.101	0.000	0.089
下楼	0.040	0.110	0.835	0.000	0.016
静止	0.000	0.000	0.001	0.990	0.009
走路	0.040	0.014	0.009	0.000	0.938

位置	ELM		SVM		BP
位置	W-ELM	S-HMM	W-SVM	S-HMM	W-BP	S-HMM
位置1	0.146	0.071	0.148	0.018	0.136	0.053
位置4	0.122	0.070	0.153	0.125	0.180	0.110
位置5	0.183	0.113	0.208	0.163	0.124	0.088
位置6	0.153	0.131	0.160	0.139	0.157	0.117
平均	0.151	0.096	0.167	0.111	0.149	0.092

位置	ELM		SVM		BP
位置	W-ELM	S-HMM	W-SVM	S-HMM	W-BP	S-HMM
位置2	0.208	0.118	0.126	0.124	0.177	0.100
位置3	0.191	0.046	0.160	0.092	0.221	0.111
位置7	0.300	0.258	0.363	0.269	0.329	0.146
位置8	0.335	0.227	0.282	0.159	0.361	0.258
平均	0.259	0.163	0.233	0.161	0.272	0.154

Identifying the confidence level of activity recognition via HMM

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