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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Mapping the Problem Space of Image Registration
Steve Oldridge, Gregor Miller and Sidney Fels
In this paper we explore a conceptual mapping of the image registration problem into an N-Dimensional problem space based on the properties of the images being registered, in contrast to traditional surveys of image registration which divide the field algorithmically. The five main dimensions of our proposed mapping are variations in: spatial alignment, intensity, focus, sensor type, and structure. Individual algorithms can be thought of as supporting a volume of solutions within the problem domain map, although they are typically designed to solve problems along a single dimension. Existing image registration papers and techniques are taxonomized within this mapping according to these major dimensions. The focus of this paper is threefold. First, an up-to-date survey of image registration techniques is provided, building from previous seminal surveys. Second, a novel taxonomy is presented that organizes the registration problem space based on the variation between the images being registered. Finally, a number of new research areas made possible under this novel taxonomy are examined, and a path is laid out for future research in the field.

Presented in St John's, May 2011 at the Canadian Conference on Computer and Robot Vision.
    author = {Steve Oldridge and Gregor Miller and Sidney Fels},
    title = {Mapping the Problem Space of Image Registration},
    booktitle = {Proceedings of the 8th Canadian Conference on Computer and Robot Vision},
    series = {CRV'11},
    pages = {309--315},
    month = {May},
    year = {2011},
    publisher = {IEEE},
    address = {New York City, New York, U.S.A.},
    isbn = {978-0-7695-4362-8},
    organization = {CIPPRS},
    location = {St. John's, Newfoundland, Canada},
    doi = {},
    url = {}