Sparse local decomposition and restructuring algorithm of joint motion sensing

Abstract

The invention discloses a sparse local decomposition and restructuring algorithm of joint motion sensing; the method includes steps of 1), calculating length of sides in a triangular mesh and size of dihedral angles corresponding to sides (the two values are recorded as LA); 2), calculating residual difference of LA vector in every triangular mesh; 3), performing sparse local decomposition on the residual difference of the LA vector and acquiring an LA base; 4), linearly mixing the LA base and acquiring a new LA vector; 5), recovering a connection mapping; 6), estimating the bid price of local orthogonality; 7), restructuring the triangular mesh. The algorithm mainly solves the problem how to perform the sparse local decomposition on a given movement mesh sequence, thereby capturing deformation of a local zone of a movement sequence; moreover, by taking it as the basis, an integrated treatment framework capable of capturing the movement zone and performing gesture edition of the triangular mesh model is structured. The sparse local decomposition and restructuring algorithm is better in locality, applicable to large-scale rotating movement and deformation, overall rotation, and good in robustness.

Description

technical field [0001] The invention relates to the fields of computer graphics and three-dimensional grid editing, in particular to a sparse local decomposition and reconstruction algorithm for joint motion perception. Background technique [0002] A dynamic geometry or animation mesh sequence is a triangular mesh with the same connection relationship, usually these triangular meshes record different poses of an object in a time sequence. This kind of geometry is very common in both animation and 3D games. Obtaining a compact representation of this triangular mesh sequence and supporting geometry editing is a very important topic in dynamic geometry processing. [0003] Traditional methods usually use a simple structure such as a skeleton or a cage (Cage) to capture the running information of a given triangle mesh sequence, and perform triangle mesh reconstruction by using skinning techniques or generalized texture coordinates. Although these methods can compress triangle...

AI Technical Summary

Problems solved by technology

[0005] The main disadvantages of the above methods are: (1) It is possible to express the triangle mesh model of the motion sequence in a relatively concise way, but it cannot provide a relatively concise way to edit the pose

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