DocumentCode :
607494
Title :
Developer-friendly segmentation using OpenVL, a high-level task-based abstraction
Author :
Miller, G. ; Fels, Sidney ; Daesik Jang
Author_Institution :
Human Commun. Technol. Lab., Univ. of British Columbia, Vancouver, BC, Canada
fYear :
2013
fDate :
15-17 Jan. 2013
Firstpage :
31
Lastpage :
36
Abstract :
Research into computer vision techniques has far out-paced the development of interfaces (such as APIs) to support the techniques´ accessibility, especially to developers who are not experts in the field. We present a new interface, specifically for segmentation methods, designed to be application-deveLoper-friendly while retaining sufficient power and flexibility to solve a wide variety of problems. The interface presents segmentation at a higher level (above algorithms) and uses a task-based description derived from definitions of low-level segmentation. We show that through interpretation, the description can be used to invoke an appropriate method to provide the developer´s requested result. Our proof-of-concept implementation interprets the model description and invokes one of six segmentation methods with automatically derived parameters, which we demonstrate on a range of segmentation tasks. We also discuss how the concepts presented for segmentation may be extended to other computer vision problems.
Keywords :
computer vision; image segmentation; OpenVL; application-developer-friendly; automatically derived parameters; computer vision techniques; developer-friendly segmentation; high-level task-based abstraction; low-level segmentation; model description; proof-of-concept implementation; segmentation methods; segmentation tasks; task-based description; Algorithm design and analysis; Computer vision; Hardware; Image color analysis; Image edge detection; Image segmentation; Libraries;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
User-Centered Computer Vision (UCCV), 2013 1st IEEE Workshop on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4673-5675-6
Electronic_ISBN :
978-1-4673-5674-9
Type :
conf
DOI :
10.1109/UCCV.2013.6530805
Filename :
6530805
Link To Document :
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