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Time and space significance visual attention method based on entropy

A technology of visual attention and information entropy, applied in the field of computer vision, it can solve problems such as areas where it is difficult for the model to detect motion, achieve good visual effects and save computing time.

Inactive Publication Date: 2010-10-06
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0007] The model proposed by Ban et al. is very superior in theory, but when the moving target is not inside the salient area, it is difficult for the model to detect the moving area

Method used

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  • Time and space significance visual attention method based on entropy
  • Time and space significance visual attention method based on entropy
  • Time and space significance visual attention method based on entropy

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Embodiment Construction

[0028] Below in conjunction with accompanying drawing and example the present invention is described in further detail.

[0029] Such as figure 1 Shown, the inventive method comprises the following steps:

[0030] (1) extract the dynamic saliency map and static saliency map in the short video;

[0031] (A) Extracting dynamic saliency maps in short videos:

[0032] (A.1) For the input short video V, take a continuous n-frame image sequence V 1 , V 2 ,...V n , in general, better experimental results can be achieved when 3≤n≤8. In order to speed up the calculation and reduce the complexity of calculation, each frame of image is converted into a lower level grayscale image. The present invention In , we choose the number of frames input in the short video as the number of grayscale levels. If the input is a color image, it is first converted into a grayscale image, and then each frame is converted from 256 grayscales to n grayscales (nk The coordinate point (x, y) in (1≤k≤n)...

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Abstract

The invention discloses a time and space significance visual attention method based on entropy, which comprises the following steps that: (1) a dynamic significance figure and a static significance figure in short video are extracted; (2) the static significance figure and the dynamic significance figure are connected to generate a final significance figure; (3) all winners win; (4) return inhibition: the pixel values of the most significant area in the final significance figure are set to be zero to obtain a novel final significance figure; and (5) attention selection. When calculating dynamic significance, the method directly calculates the dynamic significance among all frames and only calculates the static significance figure of a current frame, thereby well solving the problems of the prior art, saving the calculation time and well detecting the dynamic significance part; and in addition, the invention also applies a multi-scale method to calculate the dynamic significance so as to better calculate the dynamic significance of objects with different sizes in the video and obtain good visual effect.

Description

technical field [0001] The invention belongs to the field of computer vision, and in particular relates to a visual attention method of spatio-temporal salience based on information entropy. Background technique [0002] Visual attention methods mainly address the problem of data screening in images. In computer graphics, the content of the task is usually only a small part of the image, so it is necessary to assign different processing priorities to different image regions, which can reduce the complexity of the processing process and reduce unnecessary computational waste. In human visual information processing, we always quickly select a few salient objects for priority processing, while ignoring or discarding other non-salient objects, so that we can selectively allocate computing resources, thereby greatly improving visual information processing. efficiency, the process is called visual attention. [0003] The human visual system can easily find regions of interest a...

Claims

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Application Information

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IPC IPC(8): G06T7/20
Inventor 魏龙生桑农王岳环
Owner HUAZHONG UNIV OF SCI & TECH
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