Object recognition method based on semantic feature extraction and matching

A semantic feature and object recognition technology, applied in the field of information retrieval, can solve problems such as insufficient use of semantic information, loss of semantic information, and inappropriateness

Inactive Publication Date: 2014-08-27
武汉三际物联网络科技有限公司
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AI Technical Summary

Problems solved by technology

However, only using a single feature point in the cluster center as a description of a class of feature points does not make full use of local features, nor does it make

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  • Object recognition method based on semantic feature extraction and matching
  • Object recognition method based on semantic feature extraction and matching
  • Object recognition method based on semantic feature extraction and matching

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Embodiment Construction

[0034] 1. Semantic feature extraction part: such as figure 1 As shown, first select several pictures of a class of objects as the training library, and extract the SIFT feature points of all pictures; perform spatial clustering on all SIFT feature points through the k-means clustering algorithm, and then use the decision-making mechanism based on the kernel function to make a decision Several effective points in each spatial category are extracted; the effective points in each spatial category are trained using a support vector machine classifier, and each spatial category is trained to have a visual word with semantic features, and finally a class of objects that can be described is extracted Visual vocabulary of semantic features; select training pictures of multiple types of objects, extract the visual vocabulary of each type of object, and form a visual vocabulary of multiple types of objects.

[0035] 2. Semantic feature matching part: such as figure 2 As shown, first e...

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Abstract

The invention provides an object recognition method based on semantic feature extraction and matching and belongs to the field of information retrieval. The object recognition method based on semantic feature extraction and matching includes semantic feature extraction and semantic feature matching. The semantic feature extraction includes firstly extracting SIFT (Scale Invariant Feature Transform) feature points of training images of a class of objects, then performing spatial clustering on the SIFT feature points through k- means clustering, deciding a plurality of efficient points in every space class through a decision-making mechanism based on kernel function, and finally training the efficient points in every space class through a support vector machine classifier; a visual word with semantic features is trained from every space class, and finally a visual vocabulary describing the semantic features of a class of objects is extracted. The semantic feature matching includes firstly extracting SIFT feature points of an image of an object to be detected as the semantic description of the object to be detected, then using the support vector machine classifier for matching and classifying the semantic description of the object to be detected and visual vocabularies of classes of objects, and finally counting a histogram of the visual vocabulary of the object to be detected for determining the class of the object to be detected.

Description

technical field [0001] The invention belongs to the field of information retrieval, and in particular relates to an object recognition method based on semantic feature extraction and matching. Background technique [0002] The essence of object recognition is to establish a computing system that can identify the object category of interest in the image, which has a wide range of application requirements in real life, and has very high application value and research significance. In recent years, with the continuous maturity of pattern classification technology and the continuous development of artificial intelligence, object recognition technology based on semantic feature extraction has gradually been favored by scholars. The semantic feature of an object is to extract the local features of a class of objects, and then transform the local features into semantic information describing a class of objects according to certain processing criteria, forming a semantic feature mod...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/5838
Inventor 艾浩军艾雄军艾晓敏
Owner 武汉三际物联网络科技有限公司
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