A Method of Extracting Visual Salient Regions Based on Monocular Depth Map

Abstract

The invention discloses a method for extracting a visually salient region based on a monocular depth map, which includes the following steps: segmenting the original image to obtain each superpixel; establishing a feature vector of each superpixel, that is, estimating the scene in the image The absolute depth feature of the absolute depth; use the Gauss-Markov random field model to establish a probability model, and calculate the distance relationship between the superpixel feature vector and the adjacent superpixel feature vector through the probability model, in the absolute depth feature The relative depth feature is obtained on the basis, and the depth value of the superpixel and the depth map are obtained at the same time; the salient value of the superpixel is calculated; the gain coefficient is calculated from the depth value, and the salient value is corrected by the gain coefficient. The extraction method of the present invention can quickly and accurately automatically identify salient objects in an image without any prior knowledge, has good universality, and can detect salient regions accurately.

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...

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

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