Machine learning for activity recognition

Technical Report

Public Deposited

Citeable URL: https://ir.library.oregonstate.edu/concern/technical_reports/0r967495v

Descriptions

Attribute Name	Values
Creator	Oregon State University. Dept. of Computer Science Shen, Jianqiang
Abstract	This paper surveys the activity recognition task from a machine learning perspective. I give a definition of this problem, and I classify different activity recognition problems into two categories. I show the activities can be hierarchical, and based on such hierarchies I synthesize a language to describe activities. I give a general criteria set to evaluate activity recognition methods. I summarize some off-the-shelf machine learning methods for activity recognition and evaluate them based on this criteria set. Finally, I discuss some methods that I believe can improve the activity recognition performance.
Resource Type	Research Paper
Date Available	2012-12-04T17:10:33+00:00
Date Issued	2004
Series	Technical report (Oregon State University. Department of Computer Science)
Subject	Machine learning Human activity recognition
Déclaration de droits	Copyright Not Evaluated
Publisher	Corvallis, OR : Oregon State University, Dept. of Computer Science
Peer Reviewed	No
Language	English [eng]
Replaces	http://hdl.handle.net/1957/35440

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