Appearance-based person tracking and 3D pose estimation of upper-body and head
Christoph Weinrich, Steffen Müller, Horst–Michael Groß · Common Library Network (Der Gemeinsame Bibliotheksverbund) · 2010
In the field of human-robot interaction (HRI), recognition of humans in a robot's surroundings is a crucial task.Besides the localization, the estimation of a person's 3D pose based on monocular camera images is a challenging problem on a mobile platform.For this purpose, an appearancebased approach, using a 3D model of the human upper body, has been developed end experimentally investigated.For a real time tracking, the state of the person is estimated by a particle filter tracker, which uses different observation models for evaluating pose hypotheses.The 6D body pose is modeled by 4 parameters for the torso position and orientation as well as 2 for the head pan and tilt.In order to achieve real time operation, a smooth fit value function simplifies the particle filter's convergence.Futhermore, a sparse feature based model eliminates the need for computationally expensive geometric transformations of the image, as required by conventional Active Appearance Models (AAM).The initialization problem of the pose tracker is overcome by integrating a Histograms of Oriented Gradients (HOG) detector.