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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@InProceedings{Jang:POV2011,
    author = {Daesik Jang and Gregor Miller and Sidney Fels and Steve Oldridge},
    title = {User Oriented Language Model for Face Detection},
    booktitle = {Proceedings of the 1st Workshop on Person-Oriented Vision (POV)},
    series = {WVM'11},
    pages = {21--26},
    month = {January},
    year = {2011},
    publisher = {IEEE},
    address = {New York City, New York, U.S.A.},
    isbn = {978-1-61284-036-9},
    location = {Keauhou, Kailua-Kona, Hawai'i, U.S.A.},
    doi = {http://dx.doi.org/10.1109/POV.2011.5712364},
    url = {http://www.openvl.org/papers.php?id=Jang:POV2011}
}