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Text image joint semantics analysis method based on probability theme model

A probabilistic topic model, text image technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems other than image semantic understanding

Inactive Publication Date: 2015-09-23
TIANJIN UNIV
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Problems solved by technology

The semantic understanding of text has been developed relatively mature today. There are probabilistic latent semantic analysis (PLSA) [4] [5] models and latent Dirichlet analysis (LDA) [6] models. The application of combining text and images has the probability of Topic models are applied to text enrichment [7][8][9], but none of them are aimed at semantic understanding of images

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  • Text image joint semantics analysis method based on probability theme model
  • Text image joint semantics analysis method based on probability theme model
  • Text image joint semantics analysis method based on probability theme model

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Embodiment Construction

[0035] Here, the semantic understanding of news pictures is taken as a specific example to briefly describe its best implementation mode. Of course, the present invention does not limit the category of text images.

[0036] Regarding the PLSA model for text semantic analysis, the joint probability distribution of document vocabulary is expressed as

[0037] P ( w , d ) = P ( d ) Σ z P ( w | z ) P ( z | d ) \*MERGEFORMAT(1.1)

[0038] Among them, d represents the document (document), w represents the vocabulary (word) in the document, z represents the topic of the document, P(d) represents the probability distribution of th...

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Abstract

The invention provides a text image joint semantics analysis method based on a probability theme model. The text image joint semantics analysis method comprises the following steps: collecting a great quantity of texts comprising images, carrying out proper processing on the texts and the images, and forming an image-text pairs database in an image and text one-to-one way; utilizing samples to train to obtain a joint theme distribution model used for the text image semantics analysis; for an input image to be analyzed, extracting a visual characteristic vocabulary; applying a PLSA (Probabilistic Latent Semantic Analysis) model to the image and the visual characteristic vocabulary, and combining with text image joint theme distribution to obtain theme semantics of the image to be analyzed; matching the theme semantics obtained tin the previous step with the theme of the text in the image-text pairs database to select an optimal matching text; and for the obtained matching text, combining with an input image to carry out semantics evaluation. The text image joint semantics analysis method can obtain more semantics knowledge in addition to visualized scene object information.

Description

Technical field [0001] The present invention relates to a text image semantic analysis method in the fields of computer vision, pattern analysis, artificial intelligence and the like, in particular to a text image joint semantic analysis method based on a probabilistic topic model. Background technique [0002] Image Understanding (IU) is the semantic interpretation of images. It takes the image as the object, knowledge as the core, and studies what is where in the image, the relationship between the target scenes, what scene the image is, and how to apply the scene. The input of image understanding is data, and the output is knowledge, which belongs to the high-level content in the field of image research [1] [2]. Semantics, as the basic description carrier of knowledge information, can convert the complete image content into an intuitively understandable text-like language expression, and plays a vital role in image understanding. [0003] The potential of semantic analy...

Claims

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Application Information

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IPC IPC(8): G06F17/27
Inventor 朱海龙庞彦伟
Owner TIANJIN UNIV
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