Method for automatically estimating visual significance of image and video

A salient, image-based technology, applied in the field of automatic estimation of the visual salience of image and video content, can solve problems such as uncertainty

Inactive Publication Date: 2009-07-08
PEKING UNIV
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Problems solved by technology

[0005] However, one of the main problems of the above method is that the above existing technology cannot determine which underlying features are used to calculate the saliency under which circumstances

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  • Method for automatically estimating visual significance of image and video
  • Method for automatically estimating visual significance of image and video
  • Method for automatically estimating visual significance of image and video

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Embodiment Construction

[0041] Various aspects of the present invention will be described in detail below through embodiments and in conjunction with the accompanying drawings.

[0042] figure 1 is a schematic diagram of the saliency distribution of common media. in figure 1 (a) and figure 1 (b) is an image and an image saliency distribution map; figure 1 (c) and figure 1 (d) is the sequence of videos and video saliency distribution maps.

[0043] figure 2 It is an example diagram of a saliency distribution diagram obtained by labeling video frames according to the method for obtaining training samples according to the present invention, wherein the diagrams (a)-(f) represent respectively in documentaries, advertisements, animations, news, movies, and surveillance videos Typical frames of and their saliency distribution maps (the bright areas are high saliency, the same below).

[0044] In order to estimate saliency through learning, it is necessary to find a representative mapping function o...

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Abstract

The invention relates to an image and video processing method, in particular to a method for automatically estimating vision significant degree of video content by machine learning. The method comprises the following steps: automatically dividing training samples into a plurality of types; learning each type of the training samples to obtain optimal 'sample characteristics-significant degree distribution map' mapping function, and modeling bottom characteristics of each type of the training samples; and determining which type of a sample to be estimated belongs to according to the bottom characteristics, and calculating the significant degree distribution map according to the corresponding to 'sample characteristics-significant degree distribution map' mapping function. The method can rapidly and effectively estimate vision significant degree distribution map of various kinds of multimedia information such as video and images.

Description

technical field [0001] The invention relates to a method for automatically estimating the visual salience of images and videos, in particular to a method for automatically estimating the visual salience of images and video content through machine learning techniques. Background technique [0002] With the rapid development of electronic technology, digital cameras, video cameras and other image / video acquisition equipment are rapidly popularized, and digital audio-visual products have become an important part of personal and family consumption. With the development of network communication technology, multimedia applications such as online photo sharing, digital music, digital TV, broadband video communication, Internet streaming media, and mobile multimedia are within reach. According to the "Statistical Report on China's Internet Development Status" released in July 2008, online video is one of the important ways for Chinese netizens to entertain on the Internet. As of Jun...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/66G06F17/30
CPCG06K9/00711G06K9/4671G06V20/40G06V10/462
Inventor 田永鸿李甲李远宁黄铁军高文
Owner PEKING UNIV
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