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Movement data compression method based on sparse representation

A motion data, sparse expression technology, applied in electrical components, code conversion, etc., can solve problems such as unfavorable incremental database and data change processing, and achieve the effect of good effect, efficient compression, and high compression ratio

Active Publication Date: 2013-04-03
ZHEJIANG UNIV
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Problems solved by technology

However, as mentioned above, since the motion clips collected in the motion capture process generally do not exceed a few minutes, short-duration motion sequences are more widely used, and the spliced ​​entire segment of ultra-long motion sequences is not conducive to incremental database and Handling of data changes
Unfortunately, there is still no compression method suitable for short-term long-term motion sequences

Method used

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  • Movement data compression method based on sparse representation
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  • Movement data compression method based on sparse representation

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Embodiment Construction

[0015] The specific steps of the method and the preparatory knowledge involved will be described in detail below, and the content of the present invention will become easier to understand.

[0016] 1. K-means clustering algorithm

[0017] The K-means clustering algorithm automatically divides the given n data objects into k clusters (k is the input), so that each data object is assigned to the cluster with the closest Euclidean distance. The specific implementation steps are as follows:

[0018] 1) Randomly select k objects from n data objects as the initial clustering center (the default is random selection, you can also specify k objects or specify the coordinates of k initial clustering center points. In this method, due to the needs of the automated process, Only k objects can be randomly selected, so there will be a small error in the clustering results).

[0019] 2) According to the mean value (central object) of each clustering object, calculate the distance between e...

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Abstract

The invention provides a movement data compression method based on sparse representation. The method comprises the following steps of: firstly, analyzing input movement data to generate a sparse representation dictionary; then, carrying out sparse linear representation on each frame of the movement data based on the sparse representation dictionary; and finally, utilizing a K-SVD algorithm to carry out iterative optimization on the dictionary and the sparse representation. According to the method disclosed by the invention, under the precondition of controlling a reestablishing error into a reasonable range, the higher compression ratio can be achieved and the movement data compression method is particularly suitable for compressing shorter movement data.

Description

technical field [0001] The invention relates to the fields of animation production, motion capture and machine learning, in particular to a method for compressing motion data. Background technique [0002] With the development of the animation industry, more and more motion data (the format is mainly bvh, trc, etc.) are used in animation production, and most of these data come from the motion capture system. Motion data files generally include basic information such as character model information, total frame number of motion clips, sampling rate, and a large amount of motion data information (3D coordinates or rotation angles of each joint point of the character model, depending on the file format). Because the sampling rate of motion data is generally high, the redundancy in motion data is also relatively high, and the repetition is strong. When a large amount of motion data is required, too much disk space will be consumed. Therefore, the compression of motion data becom...

Claims

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Application Information

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IPC IPC(8): H03M7/30
Inventor 肖俊齐天庄越挺
Owner ZHEJIANG UNIV
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