计算机科学
计算机视觉
人工智能
油画
抽象
特征(语言学)
计算机图形学(图像)
调色板(绘画)
绘画
图像编辑
图像(数学)
艺术
哲学
语言学
认识论
视觉艺术
操作系统
作者
Amir Semmo,Daniel Limberger,Jan Eric Kyprianidis,Jürgen Döllner
标识
DOI:10.1016/j.cag.2015.12.001
摘要
This paper presents an interactive system for transforming images into an oil paint look. The system comprises two major stages. First, it derives dominant colors from an input image for feature-aware recolorization and quantization to conform with a global color palette. Afterwards, it employs non-linear filtering based on the smoothed structure adapted to the main feature contours of the quantized image to synthesize a paint texture in real-time. Our filtering approach leads to homogeneous outputs in the color domain and enables creative control over the visual output, such as color adjustments and per-pixel parametrizations by means of interactive painting. To this end, our system introduces a generalized brush-based painting interface that operates within parameter spaces to locally adjust the level of abstraction of the filtering effects. Several results demonstrate the various applications of our filtering approach to different genres of photography.
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