Video Analytics

What is Video Analytics?


Video Analytics, also referred to as Video Content Analysis (VCA), is a generic term used to describe computerized processing and analysis of video streams. Computer analysis of video is currently implemented in a variety of fields and industries, however the term “Video Analytics” is typically associated with analysis of video streams captured by surveillance systems. Video Analytics applications can perform a variety of tasks ranging from real-time analysis of video for immediate detection of events of interest, to analysis of pre-recorded video for the purpose of extracting events and data from the recorded video.
Relying on Video Analytics to automatically monitor cameras and alert for events of interest is in many cases much more effective than reliance on a human operator, which is a costly resource with limited alertness and attention. Various research studies and real-life incidents indicate that an average human operator of a surveillance system, tasked with observing video screens, cannot remain alert and attentive for more than 20 minutes. Moreover, the operator’s ability to monitor the video and effectively respond to events is significantly compromised as time goes by.
Furthermore, there is often a need to go through recorded video and extract specific video segments containing an event of interest. This need is growing as the use of video surveillance becomes more widespread and the quantity of recorded video increases. In some cases, time is of the essence, and such review must be undertaken in an efficient and rapid manner. Surveillance system users are also looking for additional ways to leverage their recorded video, including by extracting statistical data for business intelligence purposes. Analyzing recorded video is a need that can rarely be answered effectively by human operators, due to the lengthy process of manually going through and observing the recorded video and the associated manpower cost for this task.
While the necessity for, and benefits of, surveillance systems are undisputed, and the accompanying financial investment in deploying such surveillance system is significant, the actual benefit derived from a surveillance system is limited when relying on human operators alone. In contrast, the benefit accrued from a surveillance system can be significantly increased when deploying Video Analytics.
Video Analytics is an ideal solution that meets the needs of surveillance system operators, security officers, and corporate managers, as they seek to make practical and effective use of their surveillance systems.

What is Video Analytics Used For?


Video surveillance systems are typically installed to record video footage of areas of interest within a facility, around its perimeter or in outdoor areas which require observation, with a view to “catching” (allowing the user to be able to observe) and recording events related to security, safety, loss prevention, operational efficiency and even business intelligence.
Video Analytics enhances video surveillance systems by performing the tasks of real-time event detection, post-event analysis and extraction of statistical data while saving manpower costs and increasing the effectiveness of the surveillance system operation.
Video Analytics for Real-Time Detections & Alerts
Through the implementation of various image processing algorithms, Video Analytics can detect a variety of events, in real-time, such as:
  • Penetration of unauthorized people / vehicles into restricted areas
  • Tailgating of people / vehicles through secure checkpoints
  • Traffic obstacles
  • Unattended objects
  • Vehicles stopped in no-parking zones, highways or roads
  • Removal of assets
  • Crowding or grouping
  • Loitering
And more.
By defining the set of events that the surveillance system operator wants to be alerted to, the Video Analytics software continuously analyzes the video in real-time and provides an immediate alert upon detection of a relevant event.
savVi, Agent Vi’s unified video analytics platform, can detect a wide variety of events relating to people, vehicles or static objects – in real-time – and generate alerts according to the definitions and preferences of the surveillance system operator.
Video Analytics for Investigation (Video Search)
Video Analytics algorithms may be implemented to analyze recorded video, a task that is challenging and time consuming for a human operator, especially in cases whereby a large amount of video must be reviewed. Through rapid analysis of recorded video, Video Analytics can pinpoint an event in recorded video, and retrieve the relevant video segment from the stored video.
Through the use of search queries, the surveillance system operator defines the event desired in a specific segment of recorded video. The Video Analytics system analyzes the video and provides the search results through an automated search, without requiring any additional intervention from the operator.
savVi can analyze recorded video and present results in seconds. Various options are available to view the search results, including via thumbnails with option to playback the video of the search results, video summary in order to quickly review all search results, motion path analysis for graphical presentation of all motion paths and more.
Video Analytics for Business Intelligence 
Video Analytics algorithms can also analyze recorded video to extract statistical and operational data. Rather than having an operator manually review the video and tally all the people or cars moving in a certain area, or checking which traffic routes are most commonly taken, Video Analytics can perform these tasks automatically. 

The surveillance system operator defines the data required as well as the time period to be analyzed, and the Video Analytics system provides results following an automatic review of the recorded video. No manual review is required by the operator.

savVi can analyze recorded video to perform a variety of statistical analysis tasks relating to people and vehicles. This valuable statistical information can be viewed in multiple formats, including numerical charts, graphs, motion paths, heat maps and more. Such data provides valuable business intelligence in an instant, allowing organizations to leverage their surveillance systems and make the most of their recorded video.


Video Analytics Architectures


Video surveillance systems typically include the following main components:
  • Video cameras
  • Network infrastructure
  • Security management solutions (Video Management Systems, Command & Control Systems etc.)
  • Storage
  • Video Analytics
Video Analytics can be implemented in three different configurations, which correlate to the evolution of the Video Analytics and surveillance technologies:
1.       Server Based Implementation
In this approach, the Video Analytics is implemented through a dedicated server that pulls the video, analyzes it, and issues the alerts or analysis results. This approach is independent of the video cameras, and therefore, is applicable to most types of surveillance systems. The main disadvantages to this approach are:
  • The Video Analytics server requires the video to be transmitted to such server, and therefore causes an increase in network traffic load;
  • The video quality being analyzed by the Video Analytics server is usually degraded due to compression and transmission effects, and therefore, the Video Analytics performance may be compromised;
  • The Video Analytics server is limited by its processing power, and can typically handle no more than 16 cameras, with only limited Video Analytics functions, which makes it unattractive to large scale surveillance installations which deploy dozens or hundreds of cameras requiring a variety of Video Analytics functionalities.
2.       Edge Based Implementation
In this approach, the Video Analytics is implemented through an IP video camera or video encoder, which must have sufficient processing power to run the Video Analytics functionality. On the surface, this approach seems ideal, however it does not perform satisfactorily in many cases as it imposes limitations on the overall surveillance system design and performance. Most edge devices still lack sufficient processing power for high-end Video Analytics requirements, and therefore such implementation compromises on either the range of functions or performance quality of the Video Analytics, or both. In addition, most surveillance installations include different types of cameras, and not all cameras are suitable for “edge based implementation” nor do all cameras support it to the same quality.
3.       Agent Vi’s Distributed Implementation
Agent Vi has a unique and patented architectural approach to Video Analytics, called “Image Processing over IP networks” (IPoIPTM). With Agent Vi’s architecture, the Video Analytics task is distributed between the edge device (which may be an IP camera or encoder) and a server. This approach optimizes the workload on the edge device and server and yields high quality analytics performance. A key benefit to Agent Vi’s distributed architecture is that a single server can run comprehensive Video Analytics functions on up to 200 cameras simultaneously. This hardware efficient camera-to-server ratio is achieved without compromising on the range and performance of the analytics functionality, which makes it especially beneficial for large scale surveillance installations. Read more about Agent Vi’s IPoIPTM distributed architecture and competitive advantages.
View a table comparing the advantages and disadvantages of different video analytics architectures.

Agent Vi's Competitive Advantage


Agent Vi’s products boast significant advantages over competing products and competing Video Analytics architectures. Agent Vi offers:
1. Comprehensive Video Analytics Solutions
Agent Vi offers a full range of analytics functionalities including real-time detections and alerts, video search and business intelligence solutions. 
2. Unique Software Architecture
Allows a single server to run Video Analytics functionalities on up to 200 cameras simultaneously. The unique software architecture makes Agent Vi’s solutions especially attractive for large scale installations where hardware costs and system design complexity are major considerations.
3. Proven Quality
With more than a decade of field experience and numerous real-world installations, Agent Vi has perfected its products, providing superb detection quality, with low False Alarm Rates and high Probability of Detection.
4. Open Architecture
Agent Vi’s open architecture approach and large number of integration partners allows for best-of-breed solutions, without limiting the surveillance system design.
5. Analytics Support for a Variety of Camera Types
Agent Vi supports a range of camera types including fixed, PTZ, megapixel and thermal cameras.
6. Unlimited Functionality
Agent Vi offers the ability to perform multiple analytics functions (real time detections and alerts, video search, business intelligence) on any camera, without requiring the installation of additional hardware.