Video Analytics in the Video Surveillance Market

Price: Starting at USD 3,000
Publish Date: 31 May 2018
Code: AN-2796
Research Type: Research Report
Pages: 21
Video Analytics in the Video Surveillance Market

The growth and expansion of the surveillance market illustrates the value and importance of video and the information it contains; to this end, it also serves as a target for new technologies and innovations. Security, threat assessment, and monitoring remain integral applications for video surveillance but the use of computer vision engenders new vectors for operators to use the data collected by their surveillance systems. This report analyzes this market potential and the applications enabled by computer vision (more commonly referred to as video analytics in the surveillance space).

Video analytics is used in applications from license plate reading to facial recognition and the latter in particular makes balancing privacy and the intended use case an ongoing balancing act. Surveillance of people (the other main categories being objects and vehicles/automotive) potentially represents the most invasive (reference to privacy) not only because it can be used to identify individuals (along with their actions captured in the video) but the information can also be integrated with a myriad of other pieces of digital data left behind via communications, social media, online commerce, etc. With regards to this balancing act, the global market serves as a veritable test bed of varying degrees of surveillance, with some regions enforcing relatively strict guidelines (e.g. EU’s GDPR) to the Chinese government’s plan to implement one of the most pervasive surveillance societies to date.

As with the general surveillance market, video analytics is often most associated with or known for its security applications (e.g. perimeter detection/setting, object movement, detecting loitering or jaywalking, vehicle detection, tracking persons/objects/vehicles, etc.) but other industries are using video surveillance to better serve their customers, optimize sales traffic, grant access to facilities, and add a layer of personalization to services. While some implementations have yielded less than stellar results, over time the larger datasets will help improve the AI/ML process to produce more accurate end results. All of which comes full circle to the importance and value of data, which will only grow as smart cities, homes, and the IoT increasingly becomes part of our everyday lives.