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) Based Local Positioning System
Changsong Shen, Steve Oldridge and Sidney Fels
This paper presents an Open Source Vision Library (OpenVL) for hardware acceleration of video-based surveillance systems and other computer vision applications to facilitate low latency, real-time response. Our approach is inspired by the success of OpenGL in promoting the development of hardware acceleration for computer graphics. Our goal is to create OpenVL as a standard interface for computer vision applications that can work seamlessly on different software and hardware platforms supporting distributed camera arrays. It allows users to easily recover useful information about real dynamic scenes quickly, and in a portable manner across various software and hardware platforms. Finally, we implement an example surveillance system, called a Local Positioning System (LPS), to validate the critical underlying concepts of OpenVL.

Presented in Sydney, Australia, November 2006 at the Conference on Advanced Video and Signal-based Surveillance.
    author = {Changsong Shen and Steve Oldridge and Sidney Fels},
    title = {Open Source Vision Library (OpenVL) Based Local Positioning System},
    booktitle = {Proceedings of the Conference on Advanced Video and Signal-based Surveillance},
    series = {AVSS'06},
    pages = {105--110},
    month = {November},
    year = {2006},
    publisher = {IEEE},
    address = {New York City, New York, U.S.A.},
    isbn = {0-7695-2688-8},
    location = {Sydney, Australia},
    organization = {Computer Society},
    doi = {},
    url = {}