Computer Science > Robotics
[Submitted on 12 May 2020 (v1), last revised 21 Jul 2020 (this version, v3)]
Title:Making Robots Draw A Vivid Portrait In Two Minutes
View PDFAbstract:Significant progress has been made with artistic robots. However, existing robots fail to produce high-quality portraits in a short time. In this work, we present a drawing robot, which can automatically transfer a facial picture to a vivid portrait, and then draw it on paper within two minutes averagely. At the heart of our system is a novel portrait synthesis algorithm based on deep learning. Innovatively, we employ a self-consistency loss, which makes the algorithm capable of generating continuous and smooth brush-strokes. Besides, we propose a componential sparsity constraint to reduce the number of brush-strokes over insignificant areas. We also implement a local sketch synthesis algorithm, and several pre- and post-processing techniques to deal with the background and details. The portrait produced by our algorithm successfully captures individual characteristics by using a sparse set of continuous brush-strokes. Finally, the portrait is converted to a sequence of trajectories and reproduced by a 3-degree-of-freedom robotic arm. The whole portrait drawing robotic system is named AiSketcher. Extensive experiments show that AiSketcher can produce considerably high-quality sketches for a wide range of pictures, including faces in-the-wild and universal images of arbitrary content. To our best knowledge, AiSketcher is the first portrait drawing robot that uses neural style transfer techniques. AiSketcher has attended a quite number of exhibitions and shown remarkable performance under diverse circumstances.
Submission history
From: Fei Gao [view email][v1] Tue, 12 May 2020 03:02:24 UTC (4,065 KB)
[v2] Fri, 17 Jul 2020 10:23:22 UTC (4,066 KB)
[v3] Tue, 21 Jul 2020 07:20:32 UTC (4,094 KB)
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