Method for generating context descriptors of visual vocabulary

A visual vocabulary, context technology, applied in instruments, character and pattern recognition, computer components, etc., can solve problems such as low efficiency

Active Publication Date: 2016-06-15
杭州远传新业科技股份有限公司
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Problems solved by technology

Under large-scale images, Zhang reduces the false detection rate of visual vocabulary by quantifying the spat

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  • Method for generating context descriptors of visual vocabulary
  • Method for generating context descriptors of visual vocabulary
  • Method for generating context descriptors of visual vocabulary

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Embodiment Construction

[0045] The present invention will be described in detail below in conjunction with the accompanying drawings. It should be noted that the described embodiments are only for understanding of the present invention, and do not limit it in any way.

[0046] In the present invention, the processed local feature points can be represented by various descriptors, such as: SIFT (Scale-invariantfeaturetransform, scale-invariant feature transform), SURF, PCA-SIFT, etc.; but the local feature point descriptors are required to have a position , main direction, scale, and feature descriptor four information. In this embodiment, the processed local feature descriptor adopts SIFT descriptor. In the following description, the descriptor of the local feature point refers to SIFT, which is not specifically specified. In this embodiment, a method for generating context descriptors for local feature points is mainly introduced, and context descriptor verification is used to filter inaccurate visu...

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Abstract

The invention relates to a method for generating context descriptors of visual vocabulary. The method comprises following steps: off-line learning, context descriptor generating and context descriptor similarity computing. The off-line learning is used for construction of a visual vocabulary dictionary and evaluation of visual vocabulary. The step of context descriptor generating comprises following sub-steps: 1. extracting local characteristic points and quantifying characteristic descriptors; 2. selecting a context; 3. extracting characteristics of the local characteristic points of the context and generating context descriptors. The context descriptor similarity computing is used for verifying whether local characteristic points of two context descriptors match with each other according to the azimuth and principal direction of the local characteristic points of the context descriptors and consistency of the visual vocabulary, and evaluating the similarity of the two context descriptors through the summation of the inverse document frequency of matched visual vocabulary. The context descriptors established by the invention are adapted to influence brought by conversions such as image clipping, rotation and scale-zooming; the method can be applied in image retrieval and classification, etc.

Description

technical field [0001] The invention belongs to the field of computer image processing and machine vision, and relates to a method for generating context descriptors of visual vocabulary. Background technique [0002] Image analysis, recognition and retrieval based on local feature points in the image is an important way in the current image processing field. Quantizing local feature point descriptors into visual words and using bag-of-words models to represent images is an important method for current image recognition and classification. The combination of bag-of-words model and inverted index structure is currently the most effective content-based image retrieval method; this image retrieval method can cope with various edits and transformations of images, and has good robustness; in addition, visual vocabulary-based The inverted index structure can realize real-time query requirements in large-scale image databases. However, the visual vocabulary obtained through the d...

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Application Information

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IPC IPC(8): G06K9/72
CPCG06V30/268
Inventor 姚金良王小华黄孝喜杨冰谌志群王荣波陈浩杨醒龙
Owner 杭州远传新业科技股份有限公司
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