Abstract
This paper presents a shape and pose estimation method for 3D multi-part objects, the purpose of which is to easily map objects from the real world into virtual environments. In general, complex 3D multi-part objects cause undesired self-occlusion and non-rigid motion. To deal with the problem, we assume the following constraints:
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object model is represented in a tree structure consisting of deformable parts.
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connected parts are articulated at one point (called “articulation point”).
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as a 3D parametric model of the parts, we employ deformable superquadrics (we call DSQ).
To estimate the parameters from the sensory data, we use time model-space gradient method, which reduces the parameter estimation problem into solving a simultaneous linear equation. We have demonstrated that our system works well for multiple-part objects using real image data.
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Nunomaki, T., Yonemoto, S., Arita, D., Taniguchi, R., Tsuruta, N. (2000). Multi-part Non-rigid Object Tracking Based on Time Model-Space Gradients. In: Nagel, HH., Perales López, F.J. (eds) Articulated Motion and Deformable Objects. AMDO 2000. Lecture Notes in Computer Science, vol 1899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10722604_7
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DOI: https://doi.org/10.1007/10722604_7
Publisher Name: Springer, Berlin, Heidelberg
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