BRS Labs - Company Overview

Company Overview

Who is BRS

BRS Labs is a software development company that has developed a proprietary method to analyze video based on information the system has “learned” over time. BRS Labs is the only company that has been able to apply machine-learning capabilities to video analytics, thereby removing the human element from surveillance. No human is required to define parameters for the system to recognize behavior; the system reports unusual or suspicious behaviors based on memories it has acquired through observations over time. BRS Labs was founded in November 2005 and is headquartered in Houston, Texas.

What BRS Does

BRS Labs provides Cognitive (adaptive learning) Video Analytics software. In essence, the BRS system follows the human cognitive model for processing visual inputs into knowledge by combining computer vision, video analytics, and machine-learning technologies. The system takes the input from existing video security cameras (no need to change equipment); recognizes and identifies the objects in each frame and passes that data to its Machine Learning Engine. There, the system “learns” what activity is normal for each unique area viewed by each camera. It then stores these LEARNED memories, much the same way the human brain does, and refers back to them with any and all future activities observed by the camera. If any behavior falls outside of the norm, alerts are generated.

It is BRS’ ability to connect Machine Learning to Video Analytics that makes the system revolutionary. Alowing the machine to learn what is normal and what is not, without humans pre-determining and programming those behaviors, allows the BRS solution to report instantly and accurately on suspicious behavior.

Alerts generated by the system are delivered to a wide range of devices both fixed and mobile.

How BRS was Started

BRS Labs was founded Ray Davis, CEO, to address issues related to unmanned surveillance. After personally witnessing instances where unmanned surveillance cameras were deficient in adding adequate security to needed environments, and after speaking with sources in the security technology community, Ray decided to pursue this urgent market need. An all-star cast of scientists and developers were then carefully assembled to develop a next generation solution that would revolutionize how the field of video surveillance could be improved through the use of machine-learning. The BRS technical development team consists of some of the world’s most sophisticated computer-vision and machine-learning scientists and software engineers, capable of turning complex theoretical ideas into practical, market-ready solutions. Thousands of applicants were screened to build a world-class development team of engineers and scientists with PhDs in analytics, artificial and machine intelligence, spatial-temporal reasoning, and classical and quantum mathematics. Sixteen patents later, BRS Labs continues to make bold moves in the brave new world of video analytics, and to reshape the security community’s ideas of what is possible when improving physical security with this technology.

How BRS is Different

Conventional video surveillance systems are often ineffective, since they rely on people to monitor the cameras’ output, which is virtually impossible. Other Video Analytics solutions use rules-based algorithms to analyze video output and detect certain defined behaviors—but human behavior is too various for this approach to be very effective. Every environment and every scene is unique. No one is able to write enough rules to cover the infinite number of possibilities for any given video surveillance environment. Add to that the fact that, with every hard coded rule placed on the system an expediential amount of false positives (false alarms) are generated. This is why it is important to have a cognitive-based system such as BRS Labs AISight™ that is able to learn what is normal for every unique environment and then alert when there are activities that occur outside of that normal pattern. That same learning capability is also important in order to adapt to changes that may occur within any given environment over time. These two capabilities: the ability to adapt to any scene or environment and the ability to continue to improve upon its learning and alerting over time are the most important distinguishing factors of cognitive-based systems over rules-based video analytics systems. The benefits to businesses that adopt cognitive-based video analytics systems over rules-based systems can include everything from reduced cost due to less required coding and customization, increased effectiveness from reduced false positive alerting, and increased return on investment on the entire security infrastructure.

Company Overview Executive Team Industry News Press Careers Upcoming Events		Company Overview Who is BRS BRS Labs is a software development company that has developed a proprietary method to analyze video based on information the system has “learned” over time. BRS Labs is the only company that has been able to apply machine-learning capabilities to video analytics, thereby removing the human element from surveillance. No human is required to define parameters for the system to recognize behavior; the system reports unusual or suspicious behaviors based on memories it has acquired through observations over time. BRS Labs was founded in November 2005 and is headquartered in Houston, Texas. What BRS Does BRS Labs provides Cognitive (adaptive learning) Video Analytics software. In essence, the BRS system follows the human cognitive model for processing visual inputs into knowledge by combining computer vision, video analytics, and machine-learning technologies. The system takes the input from existing video security cameras (no need to change equipment); recognizes and identifies the objects in each frame and passes that data to its Machine Learning Engine. There, the system “learns” what activity is normal for each unique area viewed by each camera. It then stores these LEARNED memories, much the same way the human brain does, and refers back to them with any and all future activities observed by the camera. If any behavior falls outside of the norm, alerts are generated. It is BRS’ ability to connect Machine Learning to Video Analytics that makes the system revolutionary. Alowing the machine to learn what is normal and what is not, without humans pre-determining and programming those behaviors, allows the BRS solution to report instantly and accurately on suspicious behavior. Alerts generated by the system are delivered to a wide range of devices both fixed and mobile. How BRS was Started BRS Labs was founded Ray Davis, CEO, to address issues related to unmanned surveillance. After personally witnessing instances where unmanned surveillance cameras were deficient in adding adequate security to needed environments, and after speaking with sources in the security technology community, Ray decided to pursue this urgent market need. An all-star cast of scientists and developers were then carefully assembled to develop a next generation solution that would revolutionize how the field of video surveillance could be improved through the use of machine-learning. The BRS technical development team consists of some of the world’s most sophisticated computer-vision and machine-learning scientists and software engineers, capable of turning complex theoretical ideas into practical, market-ready solutions. Thousands of applicants were screened to build a world-class development team of engineers and scientists with PhDs in analytics, artificial and machine intelligence, spatial-temporal reasoning, and classical and quantum mathematics. Sixteen patents later, BRS Labs continues to make bold moves in the brave new world of video analytics, and to reshape the security community’s ideas of what is possible when improving physical security with this technology. How BRS is Different Conventional video surveillance systems are often ineffective, since they rely on people to monitor the cameras’ output, which is virtually impossible. Other Video Analytics solutions use rules-based algorithms to analyze video output and detect certain defined behaviors—but human behavior is too various for this approach to be very effective. Every environment and every scene is unique. No one is able to write enough rules to cover the infinite number of possibilities for any given video surveillance environment. Add to that the fact that, with every hard coded rule placed on the system an expediential amount of false positives (false alarms) are generated. This is why it is important to have a cognitive-based system such as BRS Labs AISight™ that is able to learn what is normal for every unique environment and then alert when there are activities that occur outside of that normal pattern. That same learning capability is also important in order to adapt to changes that may occur within any given environment over time. These two capabilities: the ability to adapt to any scene or environment and the ability to continue to improve upon its learning and alerting over time are the most important distinguishing factors of cognitive-based systems over rules-based video analytics systems. The benefits to businesses that adopt cognitive-based video analytics systems over rules-based systems can include everything from reduced cost due to less required coding and customization, increased effectiveness from reduced false positive alerting, and increased return on investment on the entire security infrastructure.
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