Adaptive Human Localization System and its Application: Activity Recognition in Smart Home
Date Issued
2006
Date
2006
Author(s)
Yu, Chen-Rong
DOI
en-US
Abstract
The rapid advancement in computer technology enables home automation system to provide a variety of convenient and novel services to people. Generally, locating the users' position in home environment is the key issue for context-aware services provision. There are several studies on human localization in all kinds of environments involving various sensor technologies, such as RF-ID tags or ultrasonic sensing. Those approaches require the inhabitants to wear some devices. Such approaches make the
inhabitants uncomfortable while the purpose is trying to provide convenient services to the inhabitants, which is somewhat ironic. In addition, most of these works do not consider the possible wrong information stemmed from some sensors.
In this thesis, we propose an adaptive human localization system in a Smart Home. Our approach uses sensory floor to perceive the weight of the inhabitants and cameras to perceive appearance of the inhabitants, so there is no need for inhabitants to wear any devices on them. By integrating multiple sensors, the localization system
will be more robust to sensor errors. In addition, we apply the kernel particle filter technique to enhance the performance in multi-target tracking. Thus, our system
will automatically determine the number of inhabitants in the environment and their corresponding locations.
An application of our localization system, activity recognition is also shown in this thesis. By collecting the context information, especially the location information, we would like to recognize the activities of daily living in the smart home.
Subjects
活動辨識
定位
粒子濾波器
activity recognition
localization
particle filter
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-95-R93922093-1.pdf
Size
23.31 KB
Format
Adobe PDF
Checksum
(MD5):c0e5ebd791118b4c4b991d37249a109e