An Efficient Moving Detection Methodology in Mobile Cloud Environment
Chang‐Hee Cho, Sanghyun Park, Jinsul Kim, Sang-Joon Lee · 2014
In this paper, an optimal motion-sensing technique of indoor children's accident prevention system has been developed. There is a drawback in the existing detection algorithm due to the environment in a manner that recognizes the difference between the 1% and more frames of motion recognition accuracy. The proposed motion detection method is based on the background modeling technique to improve the accuracy. The method is obtained using the technique to solve the recognition errors arising from the surrounding environment. We are easy to recognize the danger area using mobile cloud-based smartphone, and provide notification to tell, remote control when children access to danger area. Also, for people to recognize the size of the minimum recognition (blob) to be able to adjust the children and to recognize accurately, we improve the existing algorithms. Through the experiments, based on an improved algorithm, we derived the optimal value for children.