Y. Yang, G. Sundaramoorthi
International Conference on Computer Vision, pp. 201-208, (2013)
We present a method to track the precise shape of a dynamic object in
video. Joint dynamic shape and appearance models, in which a template of
the object is propagated to match the object shape and radiance in the
next frame, are advantageous over methods employing global image
statistics in cases of complex object radiance and cluttered background.
In cases of complex 3D object motion and relative viewpoint change,
self-occlusions and dis-occlusions of the object are prominent, and
current methods employing joint shape and appearance models are unable
to accurately adapt to new shape and appearance information, leading to
inaccurate shape detection. In this work, we model self-occlusions and
dis-occlusions in a joint shape and appearance tracking framework.
Experiments on video exhibiting occlusion/dis-occlusion, complex
radiance and background show that occlusion/dis-occlusion modeling leads
to superior shape accuracy compared to recent methods employing joint
shape/appearance models or employing global statistics.