Despite how it may be depicted on television or movie screens, reviewing surveillance footage to find evidence is a lengthy process. Sifting through hours, sometimes days, of footage is costly, time consuming, and, when done by humans, is rarely effective. Luckily, advanced technologies can save the day.
Originally, CCTV video footage was used to monitor retail stores or businesses to prevent theft, damage, or employee misconduct, and provide evidence if something were to happen. If nothing occurred, the storage would be overwritten because space was limited and the footage proved useless.
These days, storage capacity has increased and new data processing techniques make this footage extremely useful. The accessibility of recording devices with advanced features is changing the value of videos. And thanks to machine learning and video analytics, surveillance footage can be sorted and evaluated in a timely manner.
Rather than wasting time and resources having humans evaluate footage, video analytics can take care of it. Video analytics is the process of extracting pertinent information from video footage. It basically works like image analytics, but goes a step further.
Image analytics can look at a still image to find patterns, anomalies, and identify faces. Video analytics can do the same, plus measure and track behaviors. Because of this, video analytics has a promising future within different industries.
The Use Of Video Analytics
Because this technology is great for identification, behavior analysis, and situational awareness, various businesses and industries can benefit greatly. Video analytics allows business owners to evaluate who visits their stores, identify peak hours, analyze customer behavior, and more. This gives businesses insight into how they can improve customer service and which deals or displays attract more customers. These types of insights can also benefit the marketing departments, as they can better understand customer demographic and tailor ads to those groups.
Video analytics can even be applied for security and law enforcement. Since body cameras for police are becoming widely adopted, these produce lots of video footage. Video analytics could make the recordings useful by adding rich tagging and indexing, making it easier to search through footage. Parsing through certain time periods and identifying persons with specific characteristics can help to develop leads and even recognize and predict different patterns.
For airports, stadiums and other major event and transportation venues, video analytics can evaluate footage and help to relieve congestion and lines. By monitoring these venues, more workers can be deployed to decrease wait times and improve customer service.
Video-Based Predictive Analytics
While still in the early stages, a new algorithm, as reported by MIT, allows a computer to predict human actions and interactions based on behaviors seconds before the action. The outlook for this algorithm is promising. As it develops, computers could eventually be taught to predict when a crime or injury may take place.
And as artificial intelligence (AI) and robotics become more feasible in our everyday lives, this type of machine learning and predictive analytics will be necessary for robots to interact with humans naturally.
An excellent example of these video analytics in action is Veenome for marketing. Its YouTube analytics tool helps advertisers choose which videos are better suited for them to display ads. Another example is Prozone for sports analytics. By analyzing video footage of the field, players’ stats can be recorded and more effective plays can be planned and executed.
These video-based predictive analytics can also help with decision-making in industries such as aviation, air traffic control, ship navigation, power plant operation, and emergency services. Accidents and crimes can be prevented, thus, potentially saving lives.
Video Gray Area
Of course, as it goes with all surveillance, privacy concerns arise. Currently, analytics where data collection does not require consent is still a gray area. Until laws are in place to protect the public as well as businesses, companies should consider employing video analytics ethically, with respect and privacy to the data and its consumers alike.
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