With the advancement of technology in various domains, many efforts have been made to design state-of-the-art classification engines using depth cameras. Being inspired by its potential of providing information at the skeleton level using a non-invasive infrared camera, many studies have been done to aid vulnerable people such as children, elderly, and people that are physically or mentally ill. However, most of these studies focus on the algorithms and processing of a single camera, and do not consider issues that are found in practical deployments. We present KinFrame, a framework that considers challenges and requirements of designing practical systems for vulnerable people and allows application developers to easily and efficiently setup large scale, multiple depth camera deployment.
['Hee Jung Yoon', 'Ho-Kyeong Ra', 'Jin-Hee Lee', 'JeongGil Ko', 'Sang Hyuk Son']
Framework for Surveillance of Vulnerable People Using Depth Camera