Automatic License Plate Recognition (ALPR) is a Senstar Symphony-based video analytic that reads license plates and other vehicle markings, and seamlessly integrates the data into the site’s security and operational processes. The analytic can be used for automating vehicle access systems such as gates and other barriers, flag vehicle in/out times in surveillance footage, notify customer management systems of client arrivals, and track vehicles crossing toll and border checkpoints.
Automatic License Plate Recognition
Integrate Vehicle Identification with Security and Business Operations
Monitor People Capacity and Occupancy Levels
Crowd Detection is a Senstar Symphony™ video analytic that estimates the number of people within a given area in real time and triggers an alarm when a specified number of people (capacity) or a specified percentage of people (occupancy) is reached. Crowd Detection is ideal for public surveillance applications where the volume of people needs to be monitored for public safety or quality of service.
Every Face Has a Story
Face Recognition is a Senstar Symphony-based video analytic that identifies known and unknown individuals. Using a combination of patented 2D to 3D pose correction technology, this analytic is designed for fast, reliable identification under real-world challenges, including lighting, angles, facial hair, pose, glasses and other occlusions, motion, crowds, and expression.
Indoor People Tracking
Advanced Object Tracking and Classification
Indoor People Tracking is a Senstar Symphony-based video analytic optimized for detecting and monitoring the movement of people within indoor environments. Typical applications include intrusion detection, wrong-way detection, people counting and customer behavior analysis. The analytic retains its extremely high accuracy even in the presence of changing light conditions and shadows. Organizations can use tracked events to trigger alarms and direct operators to specific concerns, making it the perfect addition to any video surveillance system.
Left and Removed Item Detection
Identify Suspicious Packages and Stolen Items
Left and Removed Item Detection is a Senstar Symphony-based video analytic that monitors the presence of static objects within the field of view. The analytic is optimized for indoor environments and is designed to detect the addition of new objects as well as the removal of existing ones.
Outdoor People and Vehicle Tracking
A Video Analytic That’s Not Afraid of the Weather
Outdoor People and Vehicle Tracking is a Senstar Symphony-based video analytic optimized for detecting and monitoring the movement of vehicles and people in outdoor environments. Typical applications include perimeter intrusion detection, parking lot monitoring, public safety, and wrong-way detection. The analytic retains its extremely high tracking and object classification accuracy even in the presence of challenging weather and lighting conditions. Organizations can use tracked events to trigger alarms and direct operators to specific concerns, making it the perfect addition to any video surveillance system.
Automate Your PTZ Cameras
PTZ Auto-Tracking is a Senstar Symphony-based video analytic that enables pan-tilt-zoom (PTZ) cameras to automatically zoom in and follow a person or vehicle within the field of view. PTZ Auto-Tracking can improve response capabilities during a security event by enabling the operator to focus on what is happening rather than being distracted with camera controls.
Senstar Safe Spaces™
Video Analytics Solution to Help Business Operate Safely
Senstar Safe Spaces™ is an all-in-one video analytics solution to help businesses operate safely amidst COVID-19. Consisting of the Senstar Edge Platform, a simple plug-and-play, stand-alone device with embedded software, Senstar Safe Spaces uses network cameras to verify if health and safety protocols are being followed. Face Mask Detection, Physical Distancing, Sanitization Station Monitoring, and Occupancy Counting.
Video Analytics FAQs
What Are Video Analytics?
Video analytics process video in real-time and transform it into intelligent data. They automatically generate descriptions of what is happening in the video (metadata) and are used to detect and track objects which also could be categorized as persons, vehicles and other objects in the video stream. This information forms the basis on which to perform actions, e.g. to decide if security staff should be notified, or if a higher quality recording stream should be used. Video analytics turn simple IP video into business intelligence.
Why Video Analytics?
A security guard watching a camera feed for suspicious activity is not practical with the huge volume of video produced by today’s surveillance systems. Instead, video management software (VMS) is used to monitor and manage video feeds around the clock. The metadata generated by Video analytics can be used to alert security personnel when specific events occur, enabling them to effectively manage larger volumes of video.
How Do Video Analytics Work?
Video Analytics use advanced algorithms and machine learning to monitor, analyze and manage large volumes of video. They digitally analyze video inputs; transforming them into intelligent data which help in decision-making.
How Can Video Analytics Help You?
Detect – React – Respond:
By leveraging existing video surveillance infrastructure, video analytics are a highly cost-effective means to augment security with new detection capabilities, reduce staffing requirements by directing attention to key events, automate access control and other facility functions, and collect data on customer behavior. Respond faster to issues in real-time, uncover insights in large video archives, improve compliance and privacy, get more out of your video investments, boost search through machine learning, and improve decision making.
Edge vs Server Based-Video Analytics
Video analytic software can be run locally on each camera, centrally on a video server, or in a hybrid model, on dedicated equipment located on the edge. Each approach has its own benefits and should be examined on a per-application basis.
Intelligent video analytics, AI video analytics, video content analysis, SEP, Edge analytics