Kinematic-based Markerless Human Tracking in 3D Probabilistic Occupancy Grids
R. Bem, M. Goulart, Gisele Moraes Simas, Sílvia Silva da Costa Botelho · Journal of Communication and Information Systems · 2015
Markerless human motion tracking can be employedin many applications such as automatic surveillance, motioncapture, human-machine interface and activity recognition. Thisproblem has been extensively studied in the computer visionresearch community in the last years. In this context, the presentpaper presents an approach for 3D markerless human motiontracking based on a skeletal kinematic model of the human body.This method is applied over a 3D probabilistic occupancy gridof the environment, which is constructed by means of a Bayesianfusion of images from multiple synchronized sensoring cameras.Although the use of kinematic models in 3D human tracking iswidely employed, its use over 3D probabilistic occupancy gridsstill was not vastly investigated in the literature. The experimentswere performed using a public dataset with video sequences ofpeople in motion. The results show that the method is capableof dealing adequately with the 3D markerless human motiontracking problem.