Title :
Robust 3D Shape Reconstruction from a Single Image Based on Color Structured Light
Author :
Hu, Zhengzhou ; Guan, Qiu ; Liu, Sheng ; Chen, S.Y.
Author_Institution :
Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China
Abstract :
Reconstructing 3D shapes from 2D images based on structured light is becoming an increasingly important topic in computer vision. However, low resolution and sensitive to environment illumination are the main restriction of this technology for practical application. This paper proposes a new color coded structured light technique for reconstructing object shape from a single image. This technique works by projecting a pattern of color stripes with white gaps and assigning the projected stripe color by color classification. The method can enhance the robustness with respect to uncontrolled environment illumination and color cross-talk. The stripe boundary is located accurately by local searching method. Additionally, we propose a technique to achieve dense shape reconstruction by shifting the same patterns. Practical experimental results are provided to demonstrate the performance of the proposed methods. Furthermore, 3D models with high quality and resolution were produced under uncontrolled light condition.
Keywords :
computer vision; image classification; image colour analysis; image reconstruction; image resolution; lighting; search problems; shape recognition; color classification; color coded structured light technique; color cross-talk; color structured light; computer vision; dense shape reconstruction; environment illumination; image resolution; object shape reconstruction; projected stripe color; robust 3D shape reconstruction; searching method; stripe boundary; Artificial intelligence; Colored noise; Computational intelligence; Computer vision; Educational institutions; Image reconstruction; Layout; Lighting; Robustness; Shape; color classification; color structured light; shape reconstruction; shifted one-shot patter;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.332