[1]WU Tao,DONG Xiaoli,MENG Wei,et al.Concise line portrait generation method based on semantic segmentation[J].CAAI Transactions on Intelligent Systems,2021,16(1):134-141.[doi:10.11992/tis.202101003]
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Concise line portrait generation method based on semantic segmentation
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
16
Number of periods:
2021 1
Page number:
134-141
Column:
学术论文—人工智能基础
Public date:
2021-01-05
- Title:
- Concise line portrait generation method based on semantic segmentation
- Keywords:
- semantic segmentation; region contour; edge tangent flow; concise line portrait; face line extraction; fdog; parameter adjustment
- CLC:
- TP391
- DOI:
- 10.11992/tis.202101003
- Abstract:
- Currently, mainstream line extraction algorithms have weak detection capabilities for edges with inconspicuous regional contrast, and they use an undifferentiated and unified processing strategy for all regions. The generated line drawings are often complex, which is very unfavorable for robot manipulator drawing. Given this situation, this paper proposes a concise line portrait generation based on the semantic segmentation (CLPG-SS) method. In this method, semantic segmentation is performed on the face image, and the face is divided into different regions. Edge contour and facial detail lines are extracted based on different regions, and edge tangent flow is optimized to enhance the direction information. On this basis, the line image is used to generate the harmonic image, and the optimized edge tangent flow, facial semantic segmentation results, and harmonic image are used to adjust the parameters of the line extraction method for different segmentation regions to realize the line filtering of the detail independent region and line enhancement of the detail focus region, generating a concise line portrait. The experimental results showed that the proposed CLPG-SS method could effectively extract the main contour lines of a human face, adjust the detail lines for different regions, and improve the rendering efficiency of a robot manipulator.
- References:
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Last Update:
2021-02-25