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...
Colour
Texture
Face Front
Face Profile
@InProceedings{Jang:DCCV2012,
    author = {Daesik Jang and Gregor Miller and Sidney Fels},
    title = {Transforming Cluster-Based Segmentation for Use in OpenVL by Mainstream Developers},
    booktitle = {Proceedings of the 1st International Workshop on Developer-Centred Computer Vision},
    series = {ACCV'12},
    pages = {254--265},
    month = {November},
    year = {2012},
    publisher = {Springer},
    address = {Berlin / Heidelberg, Germany},
    isbn = {978-3-642-37409-8},
    location = {Daejeon, Korea},
    doi = {http://dx.doi.org/10.1007/978-3-642-37410-4_22},
    url = {http://www.openvl.org/papers.php?id=Jang:DCCV2012}
}