Video Analytics

Keep an eye on everything and get reports & alerts.

Develop automatically analyzing video content to detect hidden patterns and activities.

Video analytics has become a new way to analyze data that has no user interactions with the systems. It has new ways to detect hidden patterns, behavior, or incidents to make smarter and wise decisions. Video analytics has given a modern form of exploring activities that otherwise are very difficult to trace. It has gained popularity in application and business which has tremendous user walkins and personal interaction.

Video analytics at McMarvin

McMarvin has a team of experts to set up automatic video analysis which can be a near real-time analysis. Inputs are taken from cameras installed at the site. Video streams are sent to on-prem or cloud servers in chunks at regular intervals. The system is made educated to trace the activities. Video streams are then converted and compared. Activities or behaviors are identified and analyzed for making decisions. Systems can be designed to send signals or alerts when video captures activity which is not in the trained data samples.

What is video analytics?

Video Analytics or Video Content Analysis is computerized video footage analysis that uses algorithms to differentiate between object types and identify certain behavior or action in real time, providing alerts and insights to users.

Video analytic key aspects

Motion Detection

  • One of the most common detections and the challenge is detecting movement. This detection helps in every aspect, like securing the premises and identifying speed. The camera that has image sensors and is using light & dark pattern can identify motions. While analyzing, data sets are trained to determine movement, and that way near to real-time detection can be detected and analyzed.

Facial Recognition

  • This is the best technique for identification. Mostly used for security and crime control. However, now a variety of other ways can be explored using this. Phone unlocking, helping differently-abled people using facial recognition, and attendance.

Object Detection and Tracking

  • Systems can be made smarter to understand objects in the camera frame and track them over some time. This helps to locate items in the mall and objects in the warehouse. Different and innovative use cases are revolving around this.

Gesture identification

  • This has gained prominence in the sports field. Players’ gameplay is recorded and analyzed. This analysis is used to improve gameplay. Apart from sports, other areas are exploring it and gaining popularity.

Sentiment identification

  • This is a combination of tracing user’s activity along with other personal details to analyze and understand the behavior and patterns of the user’s mind. This is becoming highly popular as it can influence a mass towards a common goal.

Video analytic key aspects

Industry-wise Video Analytics benefits

Outdoor Advertising and marketing

  • It’s hard right now to capture the analysis of several views for outdoor advertisement. Video analytics can come to aid for this difficulty.

Parking infrastructure

  • Systematic identification of parking space can be handled using Video analysis. It helps in infrastructure planning.

Retail counters or window shoppings

  • Improve business by observing the user’s behavior.

Banking and security

  • Face detection, anomaly activities, etc. can be identified at banks and ATMs.

Games and Sports

  • Training or coaching of athletes, improving their skills, planning strategies, and reducing their injury on the field.

Education sector

  • Increase the level of education and make it easy for students to understand.

Government and Law

  • Identification of suspicious activities in the given premises. Monitoring of law adhering.

Health/rehabilitation centers

  • Video analysis provides the ability to monitor and track improvements in patients.

Tools we use to create data Video Analytics

OpenCV Python

  • It’s a python library used for image processing and to solve computer vision problems.


  • TensorFlow is open-source software library for differentiable programming and data flow across a range of tasks. It is a math library and is also used for machine learning apps like neural networks.


  • It is a tool for video analysis and modeling. It is built on the Java framework called Open Source Physics (OSP). The purpose of its creation is to be helpful in physics education.