Classifier for Activities with Variations

Sensors

Rabih Younes¹  Mark Jones²  ThomasL. Martin² 

[1] Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA;Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA 24061, USA;

关键词: activity recognition;    classifier design;    complex activities;    activities with variation;    dataset;   

DOI  :  10.3390/s18103529

来源: DOAJ

【 摘 要 】

Most activity classifiers focus on recognizing application-specific activities that are mostly performed in a scripted manner, where there is very little room for variation within the activity. These classifiers are mainly good at recognizing short scripted activities that are performed in a specific way. In reality, especially when considering daily activities, humans perform complex activities in a variety of ways. In this work, we aim to make activity recognition more practical by proposing a novel approach to recognize complex heterogeneous activities that could be performed in a wide variety of ways. We collect data from 15 subjects performing eight complex activities and test our approach while analyzing it from different aspects. The results show the validity of our approach. They also show how it performs better than the state-of-the-art approaches that tried to recognize the same activities in a more controlled environment.

【 授权许可】

Unknown