Multiple sensors-based kernel machine learning in smart environment.
Sensor-based monitoring systems use multiple sensors to identify high-level information based on the events that take place in a monitored environment. Identification and health care are important tasks in the smart environment. This paper presents a framework for multisensory multimedia data analysis using a kernel optimization-based principal analysis for identification and health care in a smart environment. Images of faces, palmprints, and fingerprints are used to identify a person, and a wrist pulse signal is used to analyze the person's health condition. The recognition performance evaluations are implemented on the complex dataset of face, palmprint, fingerprint, and wrist pulse signals. The experimental results show that the proposed algorithms perform well for identification and heath analysis.
Department of Automatic Test and Control, Harbin Institute of Technology, Harbin 150080, China.
Jun-Bao
0000000230643918
JB
Li
Fujian Provincial Key Lab of Big Data Mining and Applications, Fujian University of Technology, Fujian 350108, China.
Jeng-Shyang
JS
Pan
D000465:Algorithms; D003878:Dermatoglyphics; D006304:Health Status; D006801:Humans; D000069550:Machine Learning; D010363:Pattern Recognition, Automated / Q000379:methods*; D011674:Pulse