Method for extracting image region of interest based on eye movement data and bottom-layer features

A region of interest and underlying feature technology, applied in the field of image recognition, can solve problems such as the large influence of brightness features, the lack of consideration of the difference in the impact of underlying features on the region of interest, and the insignificant effect of the region of interest. Area accurate and true effect

Inactive Publication Date: 2012-06-27
CENT SOUTH UNIV
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Problems solved by technology

[0006] In the existing methods for extracting image regions of interest, they are basically realized by using the underlying features such as color, brightness, and direction, but they do not consider the difference in the degree of influence of each underlying feature on the region of interest and the actual observation resu...

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  • Method for extracting image region of interest based on eye movement data and bottom-layer features
  • Method for extracting image region of interest based on eye movement data and bottom-layer features
  • Method for extracting image region of interest based on eye movement data and bottom-layer features

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Embodiment Construction

[0067] The present invention will be described in further detail below in conjunction with the drawings and specific implementation process.

[0068] The present invention proposes a method for extracting a region of interest based on eye movement data and underlying features, including: first extracting the region of interest reflecting the real semantic needs of the user based on the eye movement data obtained from the eye tracker experiment; and then extracting the region of interest by extracting The bottom-level features and the formation of the weighted combination are used to obtain the ROI of the image; finally, the ROI extracted by the two methods is compared to find the best weight combination, and it is used to extract the ROI of other common pictures of the same type.

[0069] see figure 1 , for the specific process of the present invention, first introduce the implementation details of each step.

[0070] 1. Use the eye tracker experiment to obtain the eye moveme...

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Abstract

The invention discloses a method for extracting an image region of interest based on eye movement data and bottom-layer features. On one hand, the image region of interest, namely, eye movement ROI (Region Of Interest), for reflecting human real semanteme is extracted by visual point tracking experimental data of an eye movement instrument, and on the other hand, the image region of interest, namely, feature ROI, in a general sense is extracted in a form of bottom-layer feature weighted combination, and weight combination with highest similarity, namely, optimal weight, is found out by similarity analysis of the feature ROI and the eye movement ROI. The region of interest of other image of the same type, extracted by using the weight, can more comply with the semantic demands of users.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and relates to an image region-of-interest extraction method based on eye tracker experimental data and underlying features. Background technique [0002] With the rapid development of multimedia technology and Internet technology, the image data generated in human life and scientific experiments is expanding rapidly, and it is becoming more and more difficult for people to process image information. Therefore, how to store, express, organize and manage digital image data and how to quickly and accurately find the information you need from massive, disordered pictures are prominent problems in many current application fields. The study found that the main information of the image is often only concentrated in a few areas, and often only these key areas can give people a novel feeling, thereby attracting people's attention. These key areas are the image area of ​​interest. Find out the ...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06T7/00
Inventor 邹北骥高旭陈再良刘晴
Owner CENT SOUTH UNIV
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