Native face recognition
The ROC SDK is a fully native solution, with minimal system requirements. Decrease technical risks while increasing system flexibility and control. Keep your data on your machine, no internet connection required.
Multi-platform support
The ROC SDK supports all major operating systems and computer architectures. The ROC SDK exposes a C API with wrappers for Python, Java, C# and Go. A robust command line interface even allows constructing systems from shell scripts.
Android
macOS & iOS
Linux
Windows
The ROC SDK's industry leading enrollment and comparison speeds make Rank One the best choice for analyzing real-time streaming video.
Video support
The ROC SDK makes processing and analysis of streaming video easy via its face tracking, consolidation, and clustering algorithms.
Face recognition is becoming the biometric of choice for access control and mobile payments. This heightens the need for methods to prevent false facial presentations such as a printed photo or screen replay.
Passive Liveness
The ROC SDK ships with a patent-pending method for liveness validation to help ensure that a face presented is genuine. While other anti-spoof methods require user-assisted actions or specialized hardware, Rank One's method works on commodity cameras, only requires a single frame, and does not require the user to perform any actions. Thus, you can perform both liveness and identity validation in a single face capture.
While we don't brand ourselves as an "AI" company, make no mistake, Rank One has deep roots under the widespread umbrella of AI.
Learn More...
While AI has become a popular term in business circles and pop culture, it generally lacks any specificity as to what techniques are being applied to a given problem. In many ways all face recognition algorithms developed in the past two decades were AI. However, the recent rise of convolutional neural networks and deep learning frameworks have unlocked the means to learn representations that are vastly superior to the manual representations of the past.
In terms of Rank One's intellectual roots, they are more properly described by the academic disciplines of pattern recognition (see Duda and Hart, 1973) and computer vision (see OpenCV). Rank One's team of engineers have matriculated under and collaborated with some of the leading minds in these fields, and our software bears the marks of the parsimony and precision such disciplines extol.
