Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Extraction method of visual saliency area based on monocular depth map

An extraction method and depth map technology, which are applied in the field of extraction of visual saliency regions, can solve the problems that complex image calculation is difficult to achieve satisfactory quality, large amount of calculation, blurred edges, etc., and achieve fast and accurate automatic recognition, accurate results, The effect of reducing noise interference

Inactive Publication Date: 2015-04-29
SOUTH CHINA UNIV OF TECH
View PDF8 Cites 26 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, conventional saliency algorithms can only identify the salient regions of simple images, and these conventional algorithms are difficult to achieve satisfactory quality for complex images, because the lack of consideration of object distance information will cause a large amount of calculation and blurred edges And other issues

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Extraction method of visual saliency area based on monocular depth map

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] The present invention will be further described in detail below in conjunction with the embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0031] Such as figure 1 , a method for extracting visually salient regions based on a monocular depth map, comprising steps in the following sequence:

[0032] A. Depth map calculation stage

[0033] 1. Segment the image, and classify the spatially close and similar color, brightness, and texture features in the image into a pixel block, and the number of pixels contained in these pixel blocks is the same. These blocks of pixels are called superpixels. The adjacent regions between different superpixels will have significant differences with a large probability.

[0034] 2. Establish a feature vector for each superpixel, and calculate the relationship between it and the feature vectors of adjacent superpixels. This method considers two types of feature vectors, one is...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an extraction method of a visual saliency area based on a monocular depth map. The extraction method of the visual saliency area comprises the following sequential steps: dividing an original image to obtain super pixels; building a characteristic vector of each super pixel to estimate an absolute depth characteristic of absolute depth in a scene in the image; building a probability model by using a Gaussian-Markov random field model, calculating a distance relation between the super pixel characteristic vector and an adjacent super pixel characteristic vector by virtue of the probability model to obtain a relative depth characteristic on the basis of the absolute depth characteristic and obtain depth values and depth maps of the super pixels simultaneously; calculating saliency values of the super pixels; calculating a gain coefficient according to the depth values and correcting the saliency values by using the gain coefficient. The extraction method can be used for quickly and automatically identifying the saliency objects in the image without any prior knowledge, is high in universality and can also be used for accurately detecting the saliency area.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for extracting a visually salient region based on a monocular depth map. Background technique [0002] With the development of science and technology and the improvement of computer computing performance, human beings increasingly expect computers to be able to complete computing tasks more intelligently and autonomously. Meeting this expectation will require computers to acquire the ability to understand their surroundings. Vision is the most important way for human beings to perceive external information. Salient region detection plays a key role in computer vision, image processing and other fields, and has always been a hot topic of research. [0003] Human visual perception has evolved to a higher level through long-term natural selection. The human visual system can quickly and effectively extract objects of interest from the complex external environment and resp...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/46
CPCG06T7/143G06T7/50G06T2207/10004G06V10/462
Inventor 余卫宇孙宇飞钱少惠汤瑞东于传若石育金
Owner SOUTH CHINA UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products