More Features of Face Recognition That You Should Know About

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In last week’s article, we looked at a couple of features of face recognition and face detection software. In that article, we quoted Cyber Extruder as saying that those were the 2 features that were important for the platform. In this week’s article, we will look at a few more face recognition features that you should know about for retail security. According to Face First, there are several enterprise face detection and recognition features.

With the rise in shoplifting and theft in retail stores, store owners are constantly on the lookout for more ways to provide accurate security. Recent data shows that facial recognition is one of the most popular and accurate ways to cut down on losses from theft. Because of this, more and more large retail chains are investing in face recognition, and more are expected to do so in the near future. It is important to note, however, that not all face recognition systems are created to work for this purpose. A system must have a high degree of accuracy, along with the correct feature set, in order for it to work well in retail security, etc. Here are the enterprise facial recognition features that are important for this purpose:

  1. Watchlist Service – Any face detection and recognition system should have a database of images that new data can be compared against. In retail security, this database should be a thorough list of local known criminals, especially shoplifters, but also armed robbers and other criminal types. The database should include images of such characters from not only city-wide criminal reports but also state and nationwide.
  2. Matching Algorithm That is Airtight – Face First also suggests that you use an algorithm that contains more than just a few hundred facial feature points in its detection. While most platforms only use tens or hundreds of points, an enterprise system needs to have thousands of points in order to verify the identity of a person. This will result in a much higher degree of accuracy.
  3. Scalability – The face detection and recognition program that is used for retail should be able to handle large deployments and quickly scale across hundreds of locations without flaw. A support team should ideally be in place which would take care of installing the system and optimizing the cameras.
  4. Predictive Analytics – Not only should a company or retail owner be able to identify the image of the face of a suspect, but a face detection and recognition system for enterprise should also give such information as what time the image was taken, and which store locations are finding the highest number of matches in their system. Historical data such as which customers are banned, which are suspected of theft, etc. should also be included. The data should be separated into zones, locations, groups, and other identifying tags so that crime patterns can be recognized.
  5. Built-In Protection of Privacy – Any face detection and recognition system should be built to protect the privacy of those who use it, and those who are detected by it. For this reason, it should include:
  • Data encryption – ensuring that all data is encrypted, both while the system is in use and while it is at rest.
  • Precautions against a breach – data should be stored in the system as biometric templates only and never be converted into an image in order to protect the data in case of a breach.
  • Purging of data – Any data from surveillance should be purged from the system at regular intervals in order to prevent a leak of information.
  • Protection against profiling – All face detection and recognition systems should be created to avoid profiling by age, race, national origin, or gender.

Those are a few features that are important for retailers who are interested in face recognition for their security systems.