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Human Activity Recognition using an Image Sensor and a 3-axis Accelerometer Sensor  

Nam, Yun-Young (아주대학교 유비쿼터스컨버전스연구소)
Choi, Yoo-Joo (서울벤처정보대학원대학교 컴퓨터응용기술학과)
Cho, We-Duke (아주대학교 전자공학부)
Publication Information
Journal of Internet Computing and Services / v.11, no.1, 2010 , pp. 129-141 More about this Journal
Abstract
In this paper, we present a wearable intelligent device based on multi-sensor for monitoring human activity. In order to recognize multiple activities, we developed activity recognition algorithms utilizing an image sensor and a 3-axis accelerometer sensor. We proposed a grid?based optical flow method and used a SVM classifier to analyze data acquired from multi-sensor. We used the direction and the magnitude of motion vectors extracted from the image sensor. We computed the correlation between axes and the magnitude of the FFT with data extracted from the 3-axis accelerometer sensor. In the experimental results, we showed that the accuracy of activity recognition based on the only image sensor, the only 3-axis accelerometer sensor, and the proposed multi-sensor method was 55.57%, 89.97%, and 89.97% respectively.
Keywords
Activity recognition; multi-sensor; wearable device; pattern recognition; SVM; ubiquitous;
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