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pOp: Parameter Optimization of Differentiable Vector Patterns
Procedural materials are extensively used in computer graphics, since they provide editable, resolution‐independent representation of textures. However, tuning the parameters of procedural generators to achieve a desired result remains time‐consuming for users. Recently, inverse procedural material...
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Published in: | Computer graphics forum 2022-07, Vol.41 (4), p.161-168 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Procedural materials are extensively used in computer graphics, since they provide editable, resolution‐independent representation of textures. However, tuning the parameters of procedural generators to achieve a desired result remains time‐consuming for users. Recently, inverse procedural material algorithms have been developed, exploiting differentiable rendering methods to find the parameters of a procedural model that match a target image. These approaches focus on raster textures. We propose pOp, a practical method for estimating the parameters of vector patterns, that are formed by collections of vector shapes arranged by an arbitrary procedural program. In our approach, patterns are defined as arbitrary programs, that control the translation, rotation and scale or vector graphics elements. We support elements typical of vector graphics, namely points, lines, circle, rounded rectangles, and quadratic Bèzier drawings, in multiple colors. We optimize the program parameters by automatically differentiating the signed distance field of the drawing, which we found to be significantly more reliable than using differentiable rendering of the final image. We demonstrate our method on a variety of cases, representing the variations found in structured vector patterns. |
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ISSN: | 0167-7055 1467-8659 |
DOI: | 10.1111/cgf.14595 |