Video segmentation improvement method based on OSVOS

A video segmentation and video frame technology, which is applied in the field of computer vision, can solve problems such as large-scale color distortion, missing regions, and excessive result images, and achieve the effect of improving quality and accuracy

Active Publication Date: 2020-10-16
NANJING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

OSVOS regards the video as a still image and separates it frame by frame. This feature determines that it can complete a good segmentation when the lighting is normal and the color difference between the target and the background is obvious. However, when the light is too strong, there will be large The color of the range is distorted, and bright spots appear locally; when the light is too weak, the overall will

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  • Video segmentation improvement method based on OSVOS
  • Video segmentation improvement method based on OSVOS
  • Video segmentation improvement method based on OSVOS

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Embodiment Construction

[0040] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0041] The overall flow chart of the inventive method is as figure 1 shown. Concrete implementation steps are as follows:

[0042] Step 1. Calculate the standard value of the average value of the color feature components of the first frame of the driving car, and perform preprocessing such as light intensity and color similarity analysis on the video frame image.

[0043] The RGB color space model is the most representative color model among many color models, where R, G, and B represent the red, green, and blue values ​​of the color space, respectively. By analyzing the color characteristics of the image, it can be found that under different lighting conditions, the color components of R, G, and B will change significantly. R, G, B color component calculation formula is as follows:

[0044]

[0045]

[0046]

[0047]Acc...

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Abstract

Aiming at the problems of segmentation target missing and inaccurate target marking caused by factors such as illumination and color in OSVOS, the invention provides a video segmentation improvement method based on OSVOS, and the method comprises the steps: calculating the color component of a video image under the morphological theory, comparing the color component with a standard library, and dividing the video image into a strong light condition and a weak light condition. Meanwhile, the color similarity is calculated; after being compared with a threshold value, the data is divided into asimilar condition and a dissimilar condition, wherein the two influence factors correspond to four conditions, and different processing methods are adopted for the four conditions, including hole filling of a target missing part of an OSVOS segmentation result and removal of a non-target connected region, so that the quality and accuracy of the segmentation result are improved.

Description

technical field [0001] The invention relates to the field of computer vision and underlying video segmentation technology, in particular to an OSVOS-based video segmentation improvement method. Background technique [0002] The development of deep learning has promoted the development of computer vision and successfully improved the development of related applications such as object recognition, video detection, video segmentation, etc., especially video segmentation technology. Video segmentation is widely used in medical imaging, intelligent traffic management, network education, video surveillance and other fields in people's daily life. At the same time, the development of neural network further improves the performance of target segmentation technology. Video segmentation techniques can be roughly divided into two categories, semi-supervised and unsupervised segmentation methods according to different initialization methods. Semi-supervised segmentation refers to mark...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V20/49G06V10/56G06V2201/08G06F18/25
Inventor 孙力娟钱晶晶曹莹黄欢韩崇郭剑
Owner NANJING UNIV OF POSTS & TELECOMM
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