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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OpenVL: Abstracting Vision Tasks Using a Segment-Based Language Model
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@InProceedings{Miller:CRV2013,
    author = {Gregor Miller and Steve Oldridge and Sidney Fels},
    title = {OpenVL: Abstracting Vision Tasks Using a Segment-Based Language Model},
    booktitle = {Proceedings of the 10th International Conference on Computer and Robot Vision},
    series = {CRV'13},
    pages = {},
    month = {May},
    year = {2013},
    publisher = {IEEE},
    address = {New York City, New York, U.S.A.},
    isbn = {},
    organization = {CIPPRS},
    location = {Regina, Saskatchewan, Canada},
    doi = {},
    url = {http://www.openvl.org/papers.php?id=Miller:CRV2013}
}