title: Hierarchical Activity Recognition Using Smart Watches and RGB-Depth Cameras.
abstract: Human activity recognition is important for healthcare and lifestyle evaluation. In this paper, a novel method for activity recognition by jointly considering motion sensor data recorded by wearable smart watches and image data captured by RGB-Depth (RGB-D) cameras is presented. A normalized cross correlation based mapping method is implemented to establish association between motion sensor data with corresponding image data from the same person in multi-person situations. Further, to improve the performance and accuracy of recognition, a hierarchical structure embedded with an automatic group selection method is proposed. Through this method, if the number of activities to be classified is changed, the structure will be changed correspondingly without interaction. Our comparative experiments against the single data source and single layer methods have shown that our method is more accurate and robust.
authors.affiliation: College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China. lizhen@ouc.edu.cn.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Li
authors.affiliation: College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China. weizhiqiang@ouc.edu.cn.
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Wei
authors.affiliation: College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China. huangl@ouc.edu.cn.
authors.forename: Lei
authors.initials: L
authors.lastname: Huang
authors.affiliation: College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China. zhangshugang@hotmail.com.
authors.forename: Shugang
authors.initials: S
authors.lastname: Zhang
authors.affiliation: Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. niejie@tsinghua.edu.cn.
authors.forename: Jie
authors.initials: J
authors.lastname: Nie
keywords: RGB-D; activity recognition; hierarchical structure; wearable device