Authors:
Gisele Simas
;
Rodrigo de Bem
and
Silvia Botelho
Affiliation:
Universidade Federal do Rio Grande (FURG), Brazil
Keyword(s):
Representation Model, Volumetric Reconstruction, 3D Motion Tracking.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Geometry and Modeling
;
Image-Based Modeling
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Software Engineering
;
Tracking and Visual Navigation
Abstract:
Despite the fact of 3D motion tracking has being highly explored in the computer vision researches, it still faces
some relevant challenges, such as the tracking of objects using few a priori knowledge. In this context, this
work presents the Volume Geometric Decomposition method, capable of constructing representation models
of distinct and previously unknown objects. This method is executed over a probabilistic volumetric reconstruction
of the interested objects. It adjusts the representation to the reconstructed volume, minimizing the
amount of empty space enclosed by the model. Such representation model is composed by an appearance and
a kinematic models. The former is comprised of ellipsoids and joints, while the latter is implemented through
the Loose-Limbed model, a probabilistic graphical model. The performed experiments and the obtained results
shown that the proposed method successfully constructed representation models to highly distinct and a priori
unknown objects.