3D Human Pose Estimation using 2D-Data and an Alternative Phase Space Representation
Thomas Baltzer Moeslund, Erik Granum · VBN Forskningsportal (Aalborg Universitet) · 2000
In many 3D human pose estimation applications it is desirable to be able to estimate the pose using monocular vision. The ambiguities related to this are usually handled by introducing a priori knowledge in the form of a human model. We represent the human model in a phase space spanned by its different degrees of freedom and use the analysis-by-synthesis (AbS) approach to match the phase space model with real images and thereby estimating the pose. An alternative phase space is presented which significantly reduces the size of the phase space, hence less complexity when matching of model and image data. The phase space is reduces further by constraints based on the human motor system. Due to the relatively small size of the phase space we are able to consider the entire phase space in each time-step. This means that our system may be applied to continuous pose estimation as well as initial pose estimation. The approach is based on colours and silhouettes, where the latter is used in two different schemes. Results show that the two schemes compliment each other, making the system capable of estimating the pose even during occlusion. 1