JIPS (한국정보처리학회)
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| 한글제목(Korean Title) |
Training-Free Fuzzy Logic Based Human Activity Recognition |
| 영문제목(English Title) |
Training-Free Fuzzy Logic Based Human Activity Recognition |
| 저자(Author) |
Eunju Kim
Sumi Helal
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| 원문수록처(Citation) |
VOL 10 NO. 03 PP. 0335 ~ 0354 (2014. 09) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
The accuracy of training-based activity recognition depends on the training procedure and the extent to which the training dataset comprehensively represents the activity and its varieties. Additionally, training incurs substantial cost and effort in the process of collecting training data. To address these limitations, we have developed a training-free activity recognition approach based on a fuzzy logic algorithm that utilizes a generic activity model and an associated activity semantic knowledge. The approach is validated through experimentation with real activity datasets. Results show that the fuzzy logic based algorithms exhibit comparable or better accuracy than other trainingbased approaches.
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| 키워드(Keyword) |
Activity Semantic Knowledge
Fuzzy Logic
Human Activity Recognition
Multi-Layer Neural Network
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| 파일첨부 |
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