Abstract
Depth from focus (DfF) is a method of estimating depth of a scene by using the information acquired through the change of the focus of a camera. Within the framework of DfF, the focus measure (FM) forms the foundation on which the accuracy of the output is determined. With the result from the FM, the role of a DfF pipeline is to determine and recalculate unreliable measurements while enhancing those that are reliable. In this paper, we propose a new FM that more accurately and robustly measures focus, which we call the "ring difference filter" (RDF). FMs can usually be categorized as confident local methods or noise robust non-local methods. RDF's unique ring-and-disk structure allows it to have the advantageous sides of both local and non-local FMs. We then describe an efficient pipeline that utilizes the properties that the RDF brings. Our method is able to reproduce results that are on par with or even better than those of the state-of-the-art, while spending less time in computation.
Original language | English |
---|---|
Title of host publication | Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2444-2453 |
Number of pages | 10 |
ISBN (Electronic) | 9781538604571 |
DOIs | |
State | Published - 6 Nov 2017 |
Event | 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 - Honolulu, United States Duration: 21 Jul 2017 → 26 Jul 2017 |
Publication series
Name | Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 |
---|---|
Volume | 2017-January |
Conference
Conference | 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 |
---|---|
Country/Territory | United States |
City | Honolulu |
Period | 21/07/17 → 26/07/17 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.