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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Open Source Vision Library (OpenVL)
Changsong Shen, Steve Oldridge, Amir Afrah and Sidney Fels
Vision APIs typically expect developers to specify how to solve a problem. Therefore state-of-the-art technologies are generally under-used due to either low awareness or time constraints. Under our what-oriented methodology for vision processing, the Open Vision Library (OpenVL) requires application developers to specify what they want the result to be, leaving the compiler/run-time implementations to determine how to do it.

Presented in Victoria, British Columbia, Canada, June 2006 at the Canadian Conference on Intelligent Systems.
BibTeX
@InProceedings{Shen:IS2006,
    author = {Changsong Shen and Steve Oldridge and Amir Afrah and Sidney Fels},
    title = {Open Source Vision Library (OpenVL)},
    booktitle = {Proceedings of the 16th Canadian Conference on Intelligent Systems},
    series = {IS'06},
    pages = {Poster},
    month = {June},
    year = {2006},
    publisher = {IS},
    location = {Victoria, British Columbia, Canada},
    url = {http://www.openvl.org/papers.php?id=Shen:IS2006}
}