Expect to see additional complex algorithms and more accurate detection methods.
What technology and industry trends should you keep an eye out for to stay ahead of the pack? In short, complex analytics are growing hotter which is made possible by the trend towards GPU co-processing. Also, the country of origin of security products is gaining more attention as tariffs and government regulations draw attention to the geographic source of equipment.
More complex analytics algorithms, such as facial recognition, require substantially more computational power than simple analytics, such as cross line detection. Until recently this attribute has made more advanced analytics and accurate detection methods impractical with available hardware platforms. With the advent and popularization of co-processing technologies, such as Graphics Processing Unit (GPU) co-processing, processing large amounts of video in a short time has recently become affordable and practical. As such, facial recognition is starting to become a reality, and facial recognition products are now penetrating the market even in commercial deployments.
Savvy consumers are incorporating advanced analytics such as facial recognition to make better use of massive amounts of video data. Facial recognition enables video surveillance to detect known persons of interest attempting to enter a secure facility; a task that’s nearly impossible for a person to accomplish. While a person can certainly look for another individual, the task becomes impractical when a long list of known persons of interest exists, and detecting all of them is important.
Each consumer segment has its own common targets for detection. Some examples of current and potential facial recognition applications include:
- Airports looking to detect terror suspects
- Casinos watching for known cheaters
- Schools identifying parents without visitation rights
- Retailers identifying known shoplifters