1. Facial Recognition [Biometric]
An EmpFinesse™ Fundamentals Solution

2. Business Context Philosophy Top Implementations of the Concept
The human face plays an important role in our social interaction, conveying people’s identity. Biometric face recognition technology has received significant attention in the recent years due to its potential for a wide variety of applications in both security enforcement and non-security applications.
Face recognition has distinct advantages over other biometric techniques because of its non-contact process and identification does not require interacting with the person.
Recognizing a familiar face accurately and almost instantly — despite the frown or smile, the new wrinkles, or beard, or added hat or glasses – involves a seemingly magical brain process, especially given the many thousands of highly similar faces in a world of billions.
At one Beijing-based KFC, no longer customer even have to say the order out loud, rather a super high-tech facial recognition system predicts it for the customer by simply scanning the face. It works by matching customer's earlier images and digging out purchase behavior, dining habits ensuring faster order processing and proactive customer satisfaction.
Driving License Processing in New Mexico, USA having a rule of Facial Profile recording and a regular match with FBI records are done against those profiles to keep he Driving as well as Criminal law and order in place all along the year. This has strengthened the law enforcement agencies to perform better. The technology allows investigators to match images from a photo or a surveillance video to databases of mug shots and driver’s licenses with accompanying identifying information.
The State of New York announced it had investigated 13,000 possible cases of identity fraud in the three years since facial recognition technology was implemented by the Department of Motor Vehicles, resulting in more than 2,500 arrests. 
The State of South Carolina has used facial recognition technology to help local law enforcement agencies identify and arrest suspects in cases involving shootings, murder, prison gang smuggling and more. 
Pinellas County, Florida, has solved hundreds of cases involving bank robbery, armed robbery and fraudulent identification, among others, by running suspect photos through facial recognition software.

3. Approach Process Technology Image Capturing Microsoft
Through Ideal Media like pre-installed cameras with right format
Through Non Ideal Media like Consumer Camera, Online Social etc.
Image Correction and Aiming for Ideal
Effective Resolution
Under or Over Exposure
Minimal Motion Awareness
Optimal Compression
No Side – Rear – Top views
As much avoidance to Hats and Sunglasses
Image Processing & Storage
Quality Enhancement
Measurement based on Nodal Points i.e. around 80 ideal nodal points across the face
Storage in Image Repository
Machine Matching
In a Image Storage of 10 Million images max search time is 10 sec
Potential matches are ranked in order of algorithmic similarity
Human Review
Adding the Subjectivity of Identifying factors on top of the objective factors from Machine Matching
Microsoft
Cognitive Services
Face API
This technology offers following features –
Face Verification – Checks if two faces belong to same person or not, with confidence score
Similar Face Search – Uses a query face to find similar-looking faces from a collection of faces
Face Grouping – Organizes faces into face groups based on their visual similarity
Face Identification – Searches specific person the face belongs to, based on user-provided person, profile and face data

4. Advanced & Detailed Biometrics
Value Delivered
Authentication
Simplified Security
Profiling
Improved Persona
Deep Learning
Advanced & Detailed Biometrics
Using Facial Recognition for System Authentication
Storage of User provided picture as reference image in repository
Grab live photo through web cam or device camera during authentication
Matching the captured image with the stored image
On successful matching, user sign in process is through
On unmatched scenario, process has to be re-run
Profile Database accepts the Image of the individual
Image Analysis predicts age, gender and other personal details
Persona data matched with predictions from Image data
Persona replenished with improved data
Very useful for Onboarding process
Special type of Machine Learning based algorithm to manage data
Handles facial data with Long Term memory and Short Team memory perspectives
Advanced and much detailed Profiling with a lot of Predictive factors injected through Deep Neural algorithm

5. Thank You