In order to meet the varying needs of this audience, several layers of guidance are provided including overall principles, general guidelines, testable success criteria and a rich collection of sufficient techniques, advisory techniques, and documented common failures with examples, resource links and code. Principles - At the top are four principles that provide the foundation for Web accessibility: See also Understanding the Four Principles of Accessibility. Guidelines - Under the principles are guidelines. The 12 guidelines provide the basic goals that authors should work toward in order to make content more accessible to users with different disabilities.
A robust facial feature tracking system
(PDF) Robust Facial Feature Tracking
Designed to test multi-label video tagging. VIRAT Video Dataset - event recognition from two broad categories of activities single-object and two-objects which involve both human and vehicles. Agriculture Aberystwyth Leaf Evaluation Dataset - Timelapse plant images with hand marked up leaf-level segmentations for some time steps, and biological data from plant sacrifice. Bell, Jonathan; Dee, Hannah M.
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Social media[ edit ] Social media platforms have adopted facial recognition capabilities to diversify their functionalities in order to attract a wider user base amidst stiff competition from different applications. Founded in , Looksery went on to raise money for its face modification app on Kickstarter. After successful crowdfunding, Looksery launched in October
FaceSDK is a high-performance, multi-platform face recognition, identification and facial feature detection solution. Serving software developers worldwide, FaceSDK is a perfect way to empower Web, desktop and mobile applications with face-based user authentication, automatic face detection and recognition. Compatible with and bit desktop environments and mobile platforms including iOS and Android, FaceSDK is easy to integrate with new or existing projects, enabling developers to create a wide variety of applications. The system detects entire faces and individual facial features, recognizes faces in still images and in real-time video streams, and allows the creation of a wide range of applications from simple automatic red-eye removal tools to biometric login solutions.