Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJARAI.2013.020106
Article Published in International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 2 Issue 1, 2013.
Abstract: Person localization is of paramount importance in an ambient intelligence environment since it is the first step towards context-awareness. In this work, we present the development of a novel system for multi-modal person localization and emergency detection in an assistive ambient intelligence environment for the elderly. Our system is based on the depth sensor and microphone array of 2 Kinect devices. We use skeletal tracking conducted on the depth images and sound source localization conducted on the captured audio signal to estimate the location of a person. In conjunction with the location information, automatic speech recognition is used as a natural and intuitive means of communication in order to detect emergencies and accidents, such as falls. Our system attained high accuracy for both the localization and speech recognition tasks, verifying its effectiveness.
Georgios Galatas, Shahina Ferdous and Fillia Makedon, “Multi-modal Person Localization And Emergency Detection Using The Kinect” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 2(1), 2013. http://dx.doi.org/10.14569/IJARAI.2013.020106