Power your products with Applied Recognition’s advanced technology and save your team years of development time, risk and cost! With over twenty years of investment in face detection, recognition and authentication, we are pleased to offer our latest FaceLocate™ software to developers for license.

Two license packages are available for purchase:

1) Server software for Amazon AWS (capable of multiple instances).

2) A client software library to pair with applications built for Windows, Mac, Android and iOS devices.

Both packages include the FaceLocate™ API, giving software developers the toolkit to integrate face detection, recognition and authentication into desktop, mobile and cloud-based applications. Our server software (bundle #1) uses a load-balancing layer and a more complex architecture that can scale to handle millions of users. The client software library (bundle #2) provides a native platform interface for compiled C++ routines.


Developers can test our software today with a free AMI (Amazon Machine Image) bundle containing all of the calls for recognition, detection and authentication in the licensed versions of our software. The free bundle allows for prototypes and app mockups; full license must be purchased to enable scaling and production projects.

For more info on licensing, please contact us at

Read more about the FaceLocate™ AMI.


The FaceLocate™ API will analyze your photos and detect faces without slowing down your software. Our face detection algorithms offer settings to assign priority to speed or accuracy when finding faces. The methods employed ensure a relatively constant scanning speed regardless of image size. Developers can also specify the minimum size of a face required by their application. Face detection can be paired with recognition or used as a stand-alone feature for your software, such as focusing in on an individual and auto-cropping faces in photographs.


Once a face is detected in your photo, it is submitted for recognition. The FaceLocate™ API matches the new face to a previously tagged face belonging to a person.  If there is no existing person to match with, the face is grouped into a ‘cluster’ (group of faces with similar features) and that allows the calling application to tag an entire cluster with one operation. Our algorithms learn as you tag more faces for each “known” person. In this fashion, the API learns to match new instances of photographs that may change over time: age, weight, hair growth, accessories, etc.


Stemming from face detection and recognition projects, we have created face authentication software for use in your desktop, mobile and cloud applications. This software can authenticate online users or refresh sessions, replace passwords and more in various areas of technology:

  • FinTech – regulatory requirements for client registration, fintrac (anti-money laundering), “know-your-client” tools, digital signatures, and account authentication for financial planners & brokers.
  • Banking – deter password & identity theft and internal fraud; improve user experience for online transactions.
  • Online Gaming – prevent undesired gamblers, under-age, addicts, and fraud; allow for large wager account authentication.
  • Digital Rights Management (DRM) – Eliminate unauthorized account sharing which results in lost revenues.


Applied Recognition boasts a seasoned multi-disciplinary development team of computing and image recognition specialists who, with Dr. K. Plataniotis and Dr. C. Studholme, have developed secrets and knowhow for the commercial implementation of face detection and recognition algorithms and theories. Our face recognition methods are world class in accuracy, speed and efficiency.
The company’s core face detection and recognition engine is comprised of proprietary algorithms that maximize accuracy and enable additional functionality. Areas of focus include: orientation compensation for handling tilted or rotated faces; illumination compensation for handling differing brightness levels; skin-tone analysis for reducing false positives; multi-pass rotation and profile face detection to provide higher detection confidence; eye detection and face alignment algorithms to drive quality recognition results; large scale comparisons of known faces to unknown faces and assigning a likeness score, dynamic thresholds to handle changes in faces over time, and clustering of like faces (unknown) to enable streamlined tagging.
Accuracy is only part of the story when it comes to applying face recognition technology to help consumers tag their photos. Another aspect that is just as important is the way the application uses face recognition suggestions and how they are presented to users. Test Mile (, an independent test company, tested all four products with a random selection of digital photos representing typical consumer smartphone and digital cameras. Test Mile tested the user experience, tracking the number of mouse clicks, time and face detection and recognition results. FotoBounce clearly won in terms of speed, accuracy and efficiency.


Applied Recognition Inc. is pleased to announce it has been awarded two new patents related to our face recognition technology. The first is from the Chinese State Intellectual Property Office (No. 200880126543.0) entitled “Method, system and computed program for identification and sharing of digital images with face signatures.” The second patent is from the Canadian Intellectual Property Office with the same title (No. CA 2711143). These patents are similar to patent No. 55755185-1US, issued to Applied Recognition by the US Patent Office in 2014. These three patents share the priority date of December 31, 2007.

The patents allow for automatic recognition of multiple known faces in photos or videos on a home or mobile computer. They embody sophisticated organization and presentation of photos or videos based on the graphical selection of known faces (by selecting thumbnail images of people). Also covered is the sharing and distribution of photos or videos in an automated fashion between “friends” who are using the same software that enables the invention. Lastly, these patents grant users of the invention the right to review the results of automatic face detection, eye detection and face recognition methods, and to correct any errors resulting from the automated process.

The company has another group of patents in various stages of approval with patent offices around the world. These address specific areas including:

• Face and portrait extraction and application thereof

• Indexing Systems Automate Using Face Recognition

• Solicited and automated search for missing persons

• Data and Visualization as a function of face recognition and person indexing

• Clustering to automate face recognition

• Metadata for improving face recognition

Applied Recognition face recognition technologies are Patent Protected by US 8,750,574, US 9,152,849, CN 200880126543, and Patent Applications Pending/Allowed.