The applications of video analytics
Analytics has undoubtedly become very popular in recent times with the huge growth in data be it business or consumer data that an organization collates from varied sources. Analytics is making big strides in helping organizations consume all of this data in a meaningful manner to further enhance their revenues, reach more users, and bring in better efficiencies amongst other benefits that accrue. However, a lot has been happening, primarily in the non-audio video (AV) analytics segments, where data in raw numbers and non AV content is curated, analysed, processed and consumed. Does this mean that video analytics does not have much value or application? Not really…in fact, if done well, video analytics have a lot more critical value in terms of tangible output that can be generated – however, it has a very niche market segment in terms of application. Also, it is quite complex to perform video analytics. As we know, even simple search results across AV content is just beginning to stabilize and mature. Video analytics is a lot more intense that a simple video search, calling for use of specialized searching, editing, processing, formatting multimedia tools. These have to work in sync with the data analysis and integration tools and formats for a meaningful response to be generated.
In terms of application, as mentioned, specific domains such as sports, medicine and healthcare, art forms including music and dance can really benefit from video analytics. Training in these disciplines especially at professional levels requires a lot of video processing for the players and performers that analytics can really help. It can help both with self-analysing and competitive analysing of performances besides learning from expert sessions. Also, areas such as CCTV monitoring, in strengthening security of varied premises in an area where video analytics can really help. Video analytics application amongst global users at large may not be worth the return on investment – for example to understand shopping patterns of users to make recommendations, primarily because video analytics is expensive and also because there is not much extra value it can add in these common use segments, in addition to what non AV analytics can bring in. That said, if technology and experience can down the line make video analytics more affordable, and mainstream, its applications will definitely evolve and branch out more.