Title :
Real-Time Specularity Detection Using Unnormalized Wiener Entropy
Author :
Qing Tian ; Clark, James J.
Author_Institution :
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
Abstract :
Specularity is a common phenomenon in the real world and can provide both challenges and opportunities for computer vision algorithms. In this paper, we propose a new method to detect specularities in real time. This method is based on an unnormalized version of the Wiener Entropy which is commonly used in audio spectral analysis. Experiment results demonstrate our proposed methodology´s efficacy in specularity detection on both natural and synthetic images. Its potential in the 3D movie industry and for helping compute stereo correspondence in the presence of specularities is described.
Keywords :
computer vision; image matching; stereo image processing; 3D movie industry; audio spectral analysis; computer vision algorithms; natural images; real-time specularity detection; stereo correspondence; stereo matching; synthetic images; unnormalized Wiener entropy; Brightness; Color; Entropy; Image color analysis; Light sources; Motion pictures; Real-time systems; 3D movie; specularity detection; stereo matching; unnormalized Wiener entropy;
Conference_Titel :
Computer and Robot Vision (CRV), 2013 International Conference on
Conference_Location :
Regina, SK
Print_ISBN :
978-1-4673-6409-6
DOI :
10.1109/CRV.2013.45