Photometric Stereo Under Non-uniform Light Intensities and Exposures

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• 关键词：Photometric stereo ; Shape estimation ; Unknown light intensity and exposure ; Surface normal
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9906
• 期：1
• 页码：170-186
• 全文大小：7,293 KB
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• 作者单位：Donghyeon Cho (17)
  Yasuyuki Matsushita (18)
  Yu-Wing Tai (19)
  Inso Kweon (17)
  
  17. KAIST, Daejeon, South Korea
  18. Osaka University, Suita, Japan
  19. SenseTime Group Limited, Beijing, China
  
• 丛书名：Computer Vision – ECCV 2016
• ISBN：978-3-319-46475-6
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9906

文摘

This paper studies the effects of non-uniform light intensities and sensor exposures across observed images in photometric stereo. While conventional photometric stereo methods typically assume that light intensities are identical and sensor exposure is constant across observed images taken under varying lightings, these assumptions easily break down in practical settings due to individual light bulb’s characteristics and limited control over sensors. Our method explicitly models these non-uniformities and develops a method for accurately determining surface normal without affected by these factors. In addition, we show that our method is advantageous for general photometric stereo settings, where auto-exposure control is desirable. We compare our method with conventional least-squares and robust photometric stereo methods, and the experimental result shows superior accuracy of our method in this practical circumstance.