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...
Face Front
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A User-Oriented Language Model for Face Detection
Daesik Jang, Gregor Miller, Sidney Fels and Steve Oldridge
This paper provides a novel approach for a user-oriented language model for face detection. Even though there are many open source or commercial libraries to solve the problem of face detection, they are still hard to use because they require specific knowledge on details of algorithmic techniques. This paper proposes a high-level language model for face detection with which users can develop systems easily and even without specific knowledge on face detection theories and algorithms. Important conditions are firstly considered to categorize the large problem space of face detection. The conditions identified here are then represented as expressions in terms of a language model so that developers can use them to express various problems. Once the conditions are expressed by users, the proposed associated interpreter interprets the conditions to find and organize the best algorithms to solve the represented problem with corresponding conditions. We show a proof-of-concept implementation and some test and analyze example problems to show the ease of use and usability.

Presented in Keauhou, Kailua-Kona, January 2011 at the Workshop on Person-Oriented Vision.
    author = {Daesik Jang and Gregor Miller and Sidney Fels and Steve Oldridge},
    title = {User Oriented Language Model for Face Detection},
    booktitle = {Proceedings of the 1st Workshop on Person-Oriented Vision (POV)},
    series = {WVM'11},
    pages = {21--26},
    month = {January},
    year = {2011},
    publisher = {IEEE},
    address = {New York City, New York, U.S.A.},
    isbn = {978-1-61284-036-9},
    location = {Keauhou, Kailua-Kona, Hawai'i, U.S.A.},
    doi = {},
    url = {}