教師資料查詢 | 類別: 期刊論文 | 教師: 葛煥昭KEH HUAN-CHAO (瀏覽個人網頁)

標題:Towards a Clustering Guided Hierarchical Framework for Sensor‐Based Activity Recognition
學年110
學期1
出版(發表)日期2021/10/20
作品名稱Towards a Clustering Guided Hierarchical Framework for Sensor‐Based Activity Recognition
作品名稱(其他語言)
著者Aiguo Wang; Shenghui Zhao; Huan‐Chao Keh; Guilin Chen; Diptendu Sinha Roy
單位
出版者
著錄名稱、卷期、頁數Sensors 21(21), 6962
摘要Human activity recognition plays a prominent role in numerous applications like smart homes, elderly healthcare and ambient intelligence. The complexity of human behavior leads to the difficulty of developing an accurate activity recognizer, especially in situations where different activities have similar sensor readings. Accordingly, how to measure the relationships among activities and construct an activity recognizer for better distinguishing the confusing activities remains critical. To this end, we in this study propose a clustering guided hierarchical framework to discriminate on-going human activities. Specifically, we first introduce a clustering-based activity confusion index and exploit it to automatically and quantitatively measure the confusion between activities in a data-driven way instead of relying on the prior domain knowledge. Afterwards, we design a hierarchical activity recognition framework under the guidance of the confusion relationships to reduce the recognition errors between similar activities. Finally, the simulations on the benchmark datasets are evaluated and results show the superiority of the proposed model over its competitors. In addition, we experimentally evaluate the key components of the framework comprehensively, which indicates its flexibility and stability.
關鍵字wearable computing;activity recognition;clustering guided
語言英文(美國)
ISSN1424-8220
期刊性質國外
收錄於SCI;
產學合作
通訊作者Huan-Chao Keh
審稿制度
國別中華民國
公開徵稿
出版型式,電子版
SDGs
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