OpenVL is the future of developer-friendly computer vision - existing vision frameworks provide access at a very low level, such as individual algorithm names (often named after their inventor), while OpenVL provides a higher-level abstraction to hide the details of sophisticated vision techniques: developers use a task-centred API to supply a description of the problem, and OpenVL interprets the description and provides a solution.

The OpenVL computer vision abstraction will support hardware acceleration and multiple platforms (mobile, cloud, desktop, console), and therefore also allows vendor-specific implementations. We are committed to making it an open API available to everyone (and hope to make it an open standard); Continue reading...
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A Conceptual Structure for Computer Vision
Gregor Miller, Sidney Fels and Steve Oldridge
The research presented in this paper represents several novel conceptual contributions to the computer vision literature. In this position paper, our goal is to define the scope of computer vision analysis and discuss a new categorisation of the computer vision problem. We first provide a novel decomposition of computer vision into base components which we term the axioms of vision. These are used to define researcher-level and developer-level access to vision algorithms, in a way which does not require expert knowledge of computer vision. We discuss a new line of thought for computer vision by basing analyses on descriptions of the problem instead of in terms of algorithms. From this an abstraction can be developed to provide a layer above algorithmic details. This is extended to the idea of a formal description language which may be automatically interpreted thus allowing those not familiar with computer vision techniques to utilise sophisticated methods.

Presented in St John's, May 2011 at the Canadian Conference on Computer and Robot Vision.
    author = {Gregor Miller and Sidney Fels and Steve Oldridge},
    title = {A Conceptual Structure for Computer Vision},
    booktitle = {Proceedings of the 8th Canadian Conference on Computer and Robot Vision},
    series = {CRV'11},
    pages = {168--174},
    month = {May},
    year = {2011},
    publisher = {IEEE},
    address = {New York City, New York, U.S.A.},
    isbn = {978-0-7695-4362-8},
    organization = {CIPPRS},
    location = {St. John's, Newfoundland, Canada},
    doi = {},
    url = {}