Authors:
Manuel Amthor
;
Daniel Haase
and
Joachim Denzler
Affiliation:
Friedrich Schiller University of Jena, Germany
Keyword(s):
Landmark Tracking, Pictorial Structures, X-ray Videography, Animal Locomotion Analysis.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
;
Tracking and Visual Navigation
Abstract:
The detailed understanding of animals in locomotion is a relevant field of research in biology, biomechanics and robotics.
To examine the locomotor system of birds in vivo and in a surgically non-invasive manner, high-speed X-ray acquisition is the state of the art.
For a biological evaluation, it is crucial to locate relevant anatomical structures of the locomotor system.
There is an urgent need for automating this task, as vast amounts of data exist and a manual annotation is extremely time-consuming.
We present a biologically motivated skeleton model tracking framework based on a pictorial structure approach which is extended by robust sub-template matching.
This combination makes it possible to deal with severe self-occlusions and challenging ambiguities.
As opposed to model-driven methods which require a substantial amount of labeled training samples, our approach is entirely data-driven and can easily handle unseen cases.
Thus, it is well suited for large scale biological appli
cations at a minimum of manual interaction.
We validate the performance of our approach based on 24 real-world X-ray locomotion datasets, and achieve results which are comparable to established methods while clearly outperforming more general approaches.
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