A Contextual Descriptor Generation Method for Visual Lexicon
A visual vocabulary and context technology, applied in instruments, computing, character and pattern recognition, etc., can solve problems such as low efficiency, and achieve the effect of improving efficiency and accuracy
Active Publication Date: 2018-12-07
杭州远传新业科技股份有限公司
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Under large-scale images, Zhang reduces the false detection rate of visual vocabulary by quantifying the spatial relationship of visual vocabulary and learning semantic distance, but the efficiency of this method is low
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[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-invariant feature transform, scale-invariant feature transform), SURF, PCA-SIFT, etc.; but local feature point descriptors are required It has four information of position, main direction, scale and feature descriptor. 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 visual w...
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The invention relates to a method for generating context descriptors of visual vocabulary. The invention includes off-line learning, context descriptor generation and context descriptor similarity calculation. Offline learning is used for the construction of visual vocabulary lexicon and the evaluation of visual vocabulary. The steps of context descriptor generation are as follows: 1. Extraction of local feature points and quantification of feature descriptors; 2. Selection of context; 3. Feature extraction of local feature points in context and generation of context descriptors. The context descriptor similarity calculation verifies whether the local feature points in the two context descriptors match according to the orientation, main direction and visual vocabulary consistency of the local feature points in the context descriptor, and through the inverse document frequency of the matched visual vocabulary and to evaluate the similarity of two context descriptors. The context descriptor constructed by the invention can adapt to the effects of transformations such as image cropping, rotation, and scale scaling, and can be used in applications such as image retrieval and classification based on visual vocabulary.
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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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