Detecting Human Head and Shoulders Trajectory in a Smart Classroom
Chunyan Li, Yulian Zhu, Zhimei Xue · International Journal of Smart Home · 2014
With the development of multimedia technology, intelligent monitoring systems, etc. smart classrooms emerged, people want to get involved through multimedia and smart technology, and thus the teachers with intelligent monitoring can get the students’ attention time, points of interest , attendance , and exam invigilation and other activities more effectively, through the student movement of the head shoulder trajectory tracking and judgment and improve the efficiency of the teacher's work and strengthen the interaction between teachers and students to improve students' learning efficiency. In this paper, we use the multimedia technology on the student's head and shoulders trajectory tracking and analysis, so as to solve the above problems, mainly divided into three phases: firstly is human face recognition, using Ababoost; secondly is to get the head and shoulders’ pose, analysis to determine the effective head and shoulder trajectory; analysis and judgment on the results after using Camshift for tracking. The experimental results show that this method has strong real-time, when the head with a partially occluded or background interference it still can get better target trajectory and movement direction for us to make better judgment and analysis.