3D model retrieval method and 3D model retrieval apparatus based on slow increment features

A slow-increment feature and 3D technology, applied in character and pattern recognition, special data processing applications, instruments, etc., can solve problems such as sudden changes in feature forms, achieve the effects of reducing difficulty, efficient and accurate retrieval results, and improving matching efficiency

Active Publication Date: 2016-02-10
TIANJIN UNIV
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

Ideally, with the gradual change of the viewing angle, the change of visual features should als

Method used

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  • 3D model retrieval method and 3D model retrieval apparatus based on slow increment features
  • 3D model retrieval method and 3D model retrieval apparatus based on slow increment features
  • 3D model retrieval method and 3D model retrieval apparatus based on slow increment features

Examples

Experimental program
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Example Embodiment

[0048] Example 1

[0049] In order to make model retrieval more accurate, it can improve the efficiency of model retrieval and reduce the influence of external factors on the visual characteristics of the view, see figure 1 , This method includes the following steps:

[0050] 101: Use supervised incremental slow feature analysis method [6] , Perform incremental slow feature extraction on the preprocessed view set;

[0051] 102: Obtain the sorting of the incremental slow features according to the extracted incremental slow features, filter the incremental slow features according to the sorting results, and generate a 3D model incremental slow feature library;

[0052] 103: Use the nearest neighbor algorithm to search and match the incremental slow feature library of the 3D model, and obtain and output objects similar to the candidate model.

[0053] Wherein, the method further includes: obtaining the 2D view set V of the objects in the database, and preprocessing the 2D view set to make ...

Example Embodiment

[0063] Example 2

[0064] The solution in Embodiment 1 will be described in detail below in conjunction with specific calculation formulas and examples, as detailed below:

[0065] 201: Obtain a 2D view set V of objects in the database;

[0066] This method mainly applies retrieval technology based on image comparison, that is, 3D models are collected from multiple perspectives to form 2D view sets, and mature 2D technologies are used to extract features of objects. Therefore, each 3D model is represented by multiple views, so the view set can be expressed as Where v i Represents the view set of the i-th object; D represents the feature dimension of the view; f k Represents the k-th perspective of an object; N represents the number of 3D models; M represents the number of views of each 3D model; Indicates the scope of each object's view collection.

[0067] 202: Perform standardized preprocessing on the view set to make the view sizes of all 3D models consistent;

[0068] In order to...

Example Embodiment

[0113] Example 3

[0114] In this experiment, the embodiment of the present invention uses the existing, shared online, and more commonly used Zurich Federal Institute of Technology (German name Experiments were performed on the Technische Hochschule Zürich (ETH) database and the Taiwan University of China (NTU) database. The ETH database is relatively small and the model is more standardized. It includes 80 3D models, a total of 8 categories and 10 objects in each category, which are apples and cars. , Cow, cup, puppy, horse, pear, tomato. The NTU database has a total of 549 objects, 47 categories, and the number of objects in each category varies. The database is a virtual model database. Images are captured through 3D-MAX. This laboratory uses 60 virtual cameras to acquire images from different perspectives. , Each object obtains 60 different perspective views, where the number of virtual cameras, that is, the shooting angle, can be set according to experimental requirements,...

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Abstract

The present invention discloses a 3D model retrieval method and a 3D model retrieval apparatus based on slow increment features. The method comprises: carrying out slow increment feature extraction to a preprocessed view set by applying a supervised slow increment feature analysis method; acquiring a sorting result of the slow increment features according to the extracted slow increment features, screening the slow increment features according to the sorting result and generating a slow increment feature library of a 3D model; and carrying out retrieval matching on the slow increment feature library of the 3D model by using a nearest neighbor algorithm to acquire and output an object that is similar to a candidate model. The apparatus comprises: an extraction module, an acquisition module, a generation module and a matching and outputting module. According to the method and the apparatus, the feature extraction difficulty of a nonrigid model is reduced, the stability and accuracy of feature extraction are improved, a good condition is provided for the subsequent 3D model retrieval, and the retrieval result is guaranteed to be more efficient and accurate.

Description

technical field [0001] The invention relates to the field of image retrieval, in particular to a 3D model retrieval method and retrieval device based on incremental slow features. Background technique [0002] With the widespread use and dissemination of 3D models, as well as the development of computer graphics and spatial visualization technology, 3D models have been used in various aspects of social life, such as virtual reality, 3D animation and games, CAD, military, molecular biology, etc. 3D model has become the fourth multimedia data type after sound, image and video. At present, there are trillions of 3D models, and a large number of 3D models are generated and disseminated every day, so there is an urgent demand for 3D model retrieval. Commonly used 3D model retrieval techniques are divided into text-based retrieval and content-based retrieval. [0003] The algorithm of text-based retrieval technology is simple, and has been quite mature after years of development...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/583G06F18/22
Inventor 刘安安苏育挺李晓雪
Owner TIANJIN UNIV
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