Abstract— For many tasks in populated environments, robots need to keep track of present and future motion states of people. Most approaches to people tracking make weak assumpti...
Matthias Luber, Johannes Andreas Stork, Gian Diego...
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Dynamic appearance is one of the most important cues for tracking and identifying moving people. However, direct modeling spatio-temporal variations of such appearance is often a ...
Hwasup Lim, Octavia I. Camps, Mario Sznaier, Vlad ...
Monitoring human motion has recently received great attention and can be used in many applications, such as human motion prediction. We present the collected data set from a body ...
Jefrey Lijffijt, Panagiotis Papapetrou, Jaakko Hol...