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F. Torres Garcia, W. Kropatsch:
"Top-down 3D Tracking and Pose Estimation of a Die Using Check-points";
Talk: CVWW 2013, 18th Computer Vision Winter Workshop, Hernstein, Austria; 2013-02-04 - 2013-02-06; in: "Proceedings of the 18th Computer Vision Winter Workshop", W. Kropatsch, F. Torres Garcia, G. Ramachandran (ed.); Prip 186/3, Wien (2013), ISBN: 978-3-200-02943-9; 102 - 109.

Real-time 3D pose estimation from monocular image
sequences is a challenging research topic. Although
current methods are able to recover 3D pose,
they require a high computational cost to process
high-resolution images in a video sequence at high
frame-rates. To address that problem, we introduce
the new concept of check-points. They are the minimum
number of points needed to detect a 3D object
motion. Our method tracks the 2D projections of the
check-points over a 2D maximum pyramid. To handle
large displacements of the object, our approach
evaluates the projection of the check-points at highest
levels of the pyramid. Moreover, it refines the
pose localization by utilizing the check-points at lowest
levels of the hierarchy. We show that just checking
a few cells per frame, our method estimates the
3D pose of the tracked object. This early version
of the method works with a specific type of object a
3D cube, with six well distinguished faces and which
salient features in all the faces are dots, a die.