In a recent blog, we saw how video analytics can be a useful solution to provide better city surveillance. Here, we will elaborate on the technical capabilities of video analytics in greater detail.
The video analytics market size is estimated to grow from USD 1.69 Billion in 2016 to USD 4.23 Billion by 2021, at an estimated CAGR of 20.2% from 2016 to 2021 (MarketsandMarkets 2016 report on global analytics market).
The adoption of key technologies like Artificial Intelligence, Edge analytics, Predictive and Reactive analytics, Machine learning algorithms, and wireless features like RFID has significantly increased the demand for video analytics in different industries like retail, city surveillance, law enforcement and fleet transportation.
As the amount of video data generated tends to be pretty huge, with no way to handle and process all of it in a short span of time using manpower alone due to limitations in human capacity, video analytics is serving as a useful asset to make generated video data more valuable.
Video analytics can be done in three different scenarios like on-board real-time analytics, offline VMS forensics and an emerging field called on-demand analytics using a cloud.
Here, we will discuss three applications where video analytics are playing a pre-eminent role.
Automated solutions, delivered by deep learning and artificial intelligence, can efficiently analyze the huge amount of data that videos generate, providing tremendously fast results.
Intelligent video analytics also use deep learning for facial recognition. A well-trained deep learning solution allows video analytics to analyze facial data more quickly by providing more accurate face detection with faster response time, thus creating a powerful method for facial recognition.
Deep learning technologies also help analyze and process vast streams of footage.
Using AI in video analytics, a number of systems will be able to communicate with each helping in taking decisions and readily catching suspicious activities or predicting them before they can happen.
With the advancement of AI, the future of video analytics is not limited to providing stagnant algorithms, but also to having the event and authorization-based alert systems. Wherein, the alerts will be sent only to an authentic person and the relevant department.
There are some situations where a camera cannot take action due to some visual obstacle that is not included in camera tampering algorithms which means video analytics will not work. The situation can be beyond the line of sight.
Combining video analytics with other advanced technologies, including Real-time Location Systems (RTLS) or Radio-frequency identification Systems (RFID), can provide the exact data or location.
Facial expressions manifest not only emotions but also allied actions, behavioral patterns and give a lot of useful data when it comes to helping industries like Law enforcement, Forensics etc. Video analytics can be achieved based on data curation, sentiment analysis, and other advanced solutions. Expressions like “happy”, “sad”, “angry”, “scared”, “surprised” or “neutral” form the basis of video analytics.
An advanced video analytics solution may contain multiple functionalities and features including:
By using intelligent video analytics with advanced technologies, we can help in enabling smarter and secured cities, Law enforcement to be more foolproof, intelligent transportation solutions, retail companies to act fast and be customer friendly, and more.
This is the age of embedding intelligence inside the machine and eInfochips is poised to take advantage of its experience in video analytics and embedded domain to help our customers come up with cutting-edge solutions.