Paper Info
Title
Life-logging of wheelchair driving on web maps for visualizing potential accidents and incidents
Abstract
Life-logging has attracted rising attention as the most fundamental elements for developing every rich software today. This paper presents computational estimation and mapping of potential accidents and incidents of wheelchairs from life-logs with a single cheap and mini-sized three-axis accelerometer mounted on a wheelchair. Wheelchair driving data was obtained by real wheelchair users driving with their wheelchair on real roads, but has the sampling time delay and noises. As a first step of computational estimation, wheelchair driving behavior was classified into moving and static action, and the moving action was divided into tough and smooth status of the ground surface. We employed Support Vector Machine for classification, and made the precise supervised data from the video of wheelchair driving. As the result of classification, estimation of moving/static was achieved 98.2% accuracy rate and estimation of tough/smooth surface was achieved 82.6% accuracy rate. From the surface estimation result, wheelchair-driving difficulty was mapped and evaluated.
Year
DOI
Venue
2012
10.1007/978-3-642-32695-0_16
PRICAI
Keywords
Field
DocType
ground surface,real wheelchair user,accuracy rate,precise supervised data,smooth surface,surface estimation result,wheelchair driving,computational estimation,real road,wheelchair driving data,web map,potential accident,life log,svm
Wheelchair,Computer vision,Computer science,Accelerometer,Support vector machine,Sampling time,Software,Artificial intelligence,Time series classification,Logging
Conference
Citations 
PageRank 
References 
4
0.51
8
Authors
2
Name
Order
Citations
PageRank
Yusuke Iwasawa12610.78
Ikuko Eguchi Yairi26714.16