Document Type
Conference Paper
Publication Date
4-2014
Publication Source
IEEE INFOCOM Workshop on Security and Privacy in Big Data
Abstract
With the explosive growth of Web-based cameras and mobile devices, billions of photographs are uploaded to the Internet. We can trivially collect a huge number of photo streams for various goals, such as 3D scene reconstruction and other big data applications. However, this is not an easy task due to the fact the retrieved photos are neither aligned nor calibrated. Furthermore, with the occlusion of unexpected foreground objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct realistic scenes. In this paper, we propose a structure-based image completion algorithm for object removal that produces visually plausible content with consistent structure and scene texture. We use an edge matching technique to infer the potential structure of the unknown region. Driven by the estimated structure, texture synthesis is performed automatically along the estimated curves. We evaluate the proposed method on different types of images: from highly structured indoor environment to the natural scenes. Our experimental results demonstrate satisfactory performance that can be potentially used for subsequent big data processing: 3D scene reconstruction and location recognition.
Inclusive pages
553-558
Document Version
Published Version
Copyright
U.S. Government work not protected by U.S. copyright
Publisher
IEEE
Place of Publication
Toronto, Canada
Peer Reviewed
yes
eCommons Citation
Yang, Jianjun; Wang, Yin; Wang, Honggang; Hua, Kun; Wang, Wei; and Shen, Ju, "Automatic Objects Removal for Scene Completion" (2014). Computer Science Faculty Publications. 50.
https://ecommons.udayton.edu/cps_fac_pub/50
Included in
Databases and Information Systems Commons, Graphics and Human Computer Interfaces Commons, Information Security Commons, Numerical Analysis and Scientific Computing Commons, OS and Networks Commons, Other Computer Sciences Commons, Programming Languages and Compilers Commons, Software Engineering Commons, Systems Architecture Commons, Theory and Algorithms Commons
Comments
Permission documentation is on file.