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A Stereo Image Segmentation Method Based on Convolutional Neural Network

A technology of convolutional neural network and stereoscopic image, which is applied in the field of stereoscopic image segmentation based on convolutional neural network, can solve the problem of poor segmentation effect of stereoscopic image occlusion area, etc., and achieve the effect of simple and convenient stereoscopic image segmentation method.

Active Publication Date: 2021-09-28
WENZHOU UNIVERSITY
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Problems solved by technology

[0010] The technical problem to be solved by the embodiments of the present invention is to provide a stereoscopic image segmentation method based on a convolutional neural network. According to the left and right views of the stereoscopic image and the segmented left view, the method uses the coherent parallax pixels in the stereoscopic parallax map Point, migrate the left segmentation map to the right segmentation map to avoid the stereo image segmentation quality overly dependent on the accuracy of the stereo disparity map, construct a convolutional neural network, generate the right view target probability map, and extract advanced features of the image to deal with stereo image occlusion The segmentation problem of the region solves the problem of poor segmentation effect of the occluded region of the stereoscopic image. According to the coherent disparity segmentation map migration pixels and the credible pixels in the target probability map, the right view segmentation initialization sampling points are synthesized, and a linear energy minimum is designed. Optimize the model, solve the right view segmentation map, and obtain high-quality stereoscopic image segmentation effect

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  • A Stereo Image Segmentation Method Based on Convolutional Neural Network
  • A Stereo Image Segmentation Method Based on Convolutional Neural Network
  • A Stereo Image Segmentation Method Based on Convolutional Neural Network

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Embodiment Construction

[0128] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0129] A convolutional neural network-based three-dimensional image segmentation method according to the present invention will be described in detail below in conjunction with the accompanying drawings: this embodiment is implemented on the premise of the technical solution of the present invention, combining detailed implementation methods and processes, but The scope of protection of the present invention is not limited to the following examples. figure 2 It is the schematic flow chart of embodiment 1, image 3It is a frame diagram of the stereoscopic image segmentation technology of the present invention. According to the left and right views of the stereoscopic image and the already segmented left view, the method migrates the left segmented image to the rig...

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Abstract

The embodiment of the present invention discloses a stereoscopic image segmentation method based on a convolutional neural network, including transferring the left segmented image to the right segmented image through coherent parallax pixels in the stereoscopic disparity image; training the convolutional neural network to extract the left The features in the view and the corresponding left segmentation map are the training set. After training, the features in the right view are extracted as input to generate the target probability map of the right view. According to the target probability map, credible pixels are extracted; according to the coherence Migrating pixels in the parallax segmentation map and trusted pixels in the target probability map, synthesizing the right view segmentation initialization sampling points; using the energy optimization model to solve the right view segmentation map, and finally binarizing the right view segmentation map to obtain The final right view segmentation result. The implementation of the present invention prevents the stereoscopic image segmentation quality from being overly dependent on the accuracy of the stereoscopic disparity map, and at the same time uses the convolutional neural network to solve the problem of poor segmentation effect of the occluded area of ​​the stereoscopic image, and obtains a high-quality stereoscopic image segmentation effect.

Description

technical field [0001] The invention belongs to the technical field of image processing, and specifically refers to a three-dimensional image segmentation method based on a convolutional neural network. Background technique [0002] Image segmentation is the technology and process of dividing an image into several specific regions with unique properties and extracting objects of interest. In the prior art, great success has been achieved for single image segmentation, but left-right consistent stereo image segmentation is still a very challenging problem. [0003] As stereoscopic images and videos have become more and more popular in recent years, the demand for stereoscopic image and video editing has gradually heated up. Stereoscopic image segmentation is a challenging and hot topic in the field of stereoscopic image and video editing. Compared with single image segmentation, stereoscopic image segmentation puts forward more requirements. The object of stereoscopic image...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11G06T7/13G06T7/194
CPCG06T2207/10012G06T2207/20081G06T2207/20084G06T2207/20228G06T7/11G06T7/13G06T7/194
Inventor 厉旭杰
Owner WENZHOU UNIVERSITY
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