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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    author = {Changsong Shen and James J. Little and Sidney Fels},
    title = {Embedded Computer Vision},
    chapter = {Towards OpenVL: Improving Real-Time Performance of Computer Vision Applications},
    series = {Advances in Computer Vision and Pattern Recognition},
    edition = {1st},
    pages = {195--218},
    year = {2008},
    editor = {Branislav Kisacanin and Shuvra S. Bhattacharyya and Sek Chai},
    publisher = {Springer},
    address = {Berlin / Heidelberg, Germany},
    isbn = {978-1-84800-303-3},
    doi = {},
    url = {}