Multi-modal region-consistent significance object detection method based on foreground and background priori

A detection method and background technology, applied in the field of computer vision, can solve problems such as reducing the accuracy rate

Active Publication Date: 2015-06-03
HANGZHOU HUICUI INTELLIGENT TECH CO LTD
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Problems solved by technology

In addition, most of the existing methods are only based on 2D images, where the same color or texture between the salient objects and the background causes the correct rate of saliency extraction to decrease

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  • Multi-modal region-consistent significance object detection method based on foreground and background priori

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Embodiment Construction

[0046] The present invention will be further described below.

[0047] A salient object detection method based on multimodal region consistency of foreground and background priors, comprising the steps of:

[0048] 1) Obtain the color image and depth image of the scene from the Kinect depth camera, and generate

[0049] into a point cloud;

[0050] 2) Use color map and depth map to segment the scene

[0051] The process of scene segmentation is as follows: According to the difference between the characteristics of different regions of the image, the image on the three channels of the color map is segmented respectively, and the intersection of these three segmentation sets is calculated, and then the depth map is used as the fourth channel, and the edge weight function is calculated at the same time The difference value between pixels in the color space and the depth space, adopts an adaptive method to determine the weight in the edge weight function.

[0052] The process o...

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Abstract

The invention discloses a multi-modal region-consistent significance object detection method based on foreground and background priori. The method comprises the following steps: 1) obtaining a color image and a depth image of a scene, while generating a point cloud; 2) using the color image and the depth image for the scene segmentation; 3) using an object region-based detection method for detecting all regions of the image to obtain a focal region, taking the focal region as foreground priori in the color image; 4) detecting a plane region of the point cloud as a background priori, obtaining point cloud data from the color image and the corresponding depth image, detecting a plane structure in the point cloud data, then calculating the boundary length of a scene connection boundary, calculating a background connectivity of plane segmentation, and obtaining over-segmentation background weight; 5) calculating to obtain a global region contrast SG(rk), obtaining a significance map through the formula below: S(rk)=SF(rk)*SB(rk)*SG(rk). The multi-modal region-consistent significance object detection method effectively improves the accuracy.

Description

technical field [0001] The invention relates to computer vision technology, in particular to an image processing and salient object detection method. Background technique [0002] Visual salience refers to subregions that are distinct from neighboring regions in the environment and can quickly attract the observer's attention. One of the most important applications of visual saliency is the fast search for salient objects from complex scenes. Many robotic systems also use visual saliency for object recognition and detection. [0003] Object detection through visual saliency, since humans always regard the object as a whole, it is hoped that the sub-regions containing the object have the same or similar saliency value, however, most existing methods use pixel-based methods to calculate saliency , the resulting saliency values ​​vary from pixel to pixel. Moreover, most of the existing methods are only based on 2D images, where the same color or texture between the salient o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 张剑华王其超谢榛赵妍珠陈胜勇张建伟
Owner HANGZHOU HUICUI INTELLIGENT TECH CO LTD
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