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: Towards a Novel Software Architecture for Computer Vision
Changsong Shen, James J. Little and Sidney Fels
This paper presents our progress on OpenVL -a novel software architecture to address efficiency through facilitating hardware acceleration, reusability and scalability for computer vision. A logical image understanding pipeline is introduced to allow parallel processing. As well, we discuss our middleware -VLUT that enables applications to operate transparently over a heterogeneous collection of hardware implementations. OpenVL works as a state machine, with an event-driven mechanism to provide users with application-level interaction. Various explicit or implicit synchronization and communication methods are supported among distributed processes in the logical pipelines. The intent of OpenVL is to allow users to quickly and easily recover useful information from multiple scenes across various software environments and hardware platforms. We implement two different human tracking systems to validate the critical underlying concepts of OpenVL.

Presented in Minneapolis, Minnesota, U.S.A., June 2007 at the Workshop on Embedded Computer Vision.
    author = {Changsong Shen and James J. Little and Sidney Fels},
    title = {OpenVL: Towards a Novel Software Architecture for Computer Vision},
    booktitle = {Proceedings of the 3rd Workshop on Embedded Computer Vision},
    series = {CVPR'07},
    pages = {1--8},
    month = {June},
    year = {2007},
    publisher = {IEEE},
    address = {New York City, New York, U.S.A.},
    isbn = {1-4244-1180-7},
    location = {Minneapolis, Minnesota, U.S.A.},
    doi = {},
    url = {}