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Motion sequence search method based on alignment clustering analysis

A technology of motion sequence and cluster analysis, which is applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of not considering the time axis order of motion sequence, and achieve the effect of improving retrieval accuracy

Inactive Publication Date: 2014-08-06
XIAN TECHNOLOGICAL UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to provide a motion sequence retrieval method based on alignment clustering analysis, which overcomes the shortcoming that the existing method does not consider the sequence of the motion sequence on the time axis when the motion sequence is segmented

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  • Motion sequence search method based on alignment clustering analysis
  • Motion sequence search method based on alignment clustering analysis
  • Motion sequence search method based on alignment clustering analysis

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Embodiment Construction

[0045] The present invention will be described in detail below in combination with specific embodiments.

[0046] First, a brief explanation of the prior art content appearing in the following content:

[0047] Quaternion: For a rigid body with a fixed point, it can achieve any attitude by rotating a certain axis around the point through a specific angle θ, and the direction of the rotation axis can be a unit vector n express: n=cos α??i+cos β??j+cos γ??k, the quaternion describing the rotation can be expressed as: q=cos θ / 2+sin θ / 2cos α??i+sin θ / 2cos β ??j+sin θ / 2cos γ??k =w+x??i+y??j+z??k.

[0048] The K-means algorithm is a hard clustering algorithm, which is a representative of a typical prototype-based objective function clustering method. It uses a certain distance from the data point to the prototype as the optimized objective function, and uses the method of finding the extreme value of the function to obtain an iterative operation. adjustment rules. The K-means al...

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Abstract

The invention relates to a motion sequence search method based on an alignment clustering analysis. According to an existing motion sequence search method, when segmenting is taken into consideration, the motion time sequence of each frame is not taken into consideration, and segmentation points cannot be accurately positioned. According to the motion sequence search method, the human body motion sequence is recorded and stored; a server end processes motion sequences to obtain the characteristics of the motion sequences, and the characteristics of all the motion sequences are combined to generate a characteristic database; the server end calculates the characteristics of the motion sequences provided by a client side; the server end matches the characteristics extracted by the motion sequences provided by the client side with the characteristics in the characteristic database, the distances between the characteristics are respectively calculated, and the motion sequences in the database are ranked and output according to the distance to serve as a retrieved result to be returned to the client side. According to the motion sequence search method based on the alignment clustering analysis, the motion characteristics are extracted on that basis and applied to the motion search, and compared with a true segmentation result, the segmentation method has efficiency.

Description

technical field [0001] The invention belongs to the technical field of multimedia information retrieval, and in particular relates to a motion sequence retrieval method based on alignment clustering analysis. Background technique [0002] Human motion is widely used in animation, game software, human-computer interaction, etc. Human motion sequences are complex both in time and in space. Therefore, it is very important to be able to effectively express the motion of the human body, describe the characteristics of the motion efficiently, and retrieve the relevant motion sequences from the database effectively. [0003] At present, there has been a probabilistic principal component analysis (PCA) algorithm to decompose the human motion sequence into obvious actions, use the geometric features of the specified joint points to segment the motion, and realize motion retrieval on this basis, but this solution There are technical defects. When considering the motion sequence seg...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/5838
Inventor 肖秦琨郑中华
Owner XIAN TECHNOLOGICAL UNIV
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