This new algorithm is in practice twice faster in sequential than the reference algorithm designed in 2000 and offers one order of magnitude speedups in parallel. A second algorithm revisits the reference sequential algorithm to compute this abstraction and is based on local propagations expressible as parallel tasks. ![]() The first algorithm developed in the context of this thesis is based on multi-thread parallelism for the contour tree computation. We propose three new efficient parallel algorithms for the computation of these abstractions on multi-core shared memory workstations. In this manuscript, we focus on three fundamental topological abstractions based on level sets: merge trees, contour trees and Reeb graphs. Topological Data Analysis requires efficient algorithms to deal with the continuously increasing size and level of details of data sets. Moreover, this paper presents validation of the proposed method in many applications, such as shape alignment, shape deformation, shape co-segmentation and shape correspondence. Quantitative and qualitative analysis and comparison show that the proposed method can generate a symmetry-aware kinematic skeleton with accurate joints and has no restrictions on the pose and orientation of the input human body model. In this way, the symmetric joints of the kinematic skeleton, e.g., the left knee joint and the right knee joint, can be distinguished. Finally, a specific local coordinate system is defined on the kinematic skeleton and is used to distinguish the symmetry of the kinematic skeleton. Then, the joints of the embedded kinematic skeleton are refined according to the geometry of the human body model and some prior knowledge. First, a template kinematic skeleton with semantics is embedded into the input human body model. In this paper, an automatic method is proposed to generate a symmetry-aware kinematic skeleton for a human body model with an arbitrary pose and orientation. Index Terms: I.3.7 (Computer Graphics): Animation- (I.3.5): Computer Graphics-Geometric algorithms, languages, and sys- tems Finally, it is efficient as our prototype implementation gen- erally takes less than 30 seconds to adapt a skeleton to a character. ![]() Furthermore, the method can be used for partial retargeting to directly attach skeleton parts to specific limbs. Together, these provide a robust retargeting that can also be tuned between the original skeleton shape and the mesh shape with intuitive weights. It proposes specific multireso- lution and symmetry approaches as well as a simple yet effective shape descriptor. Given a character mesh and a skele- ton, the method adapts the skeleton to the character by matching topology graphs between the two. While the method can be applied to simple skeletons, it also proposes a new approach that is applicable to high quality animation as it is able to deal with complex skeletons that include control bones (those that drive deforming bones). ![]() It demonstrates a method for automati- cally adapting existing skeletons to different characters. This paper presents a new approach to facilitate reuse and remix- ing in character animation.
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