Advanced Creative Technology | Anomaly Detection System
 

Anomaly Detection System

Anomaly Detection and Behavior Recognition

ACT Anomaly Detection and Behavior Recognition allows security professionals to detect and identify high-impact anomalous events as they occur.
Proactive security requires the consistent monitoring of your environment to identify disruptive threats. Incidents can often be stopped before they occur with proper identification. ACT Behavior Recognition allows security professional to identify disruptive threats and capture events as they occur. Increase the effectiveness of your security perimeter with ACT.
Proactive security requires the consistent monitoring of your environment to identify disruptive threats. Incidents can often be stopped before they occur with proper identification. Scylla Behavior Recognition allows security professional to identify disruptive threats and capture events as they occur. Increase the effectiveness of your security perimeter with Scylla.

How It Works

ACT is optimized to work on multiple video streams using a single GPU and provide real-time event tracking.

Once an anomalous event has been recognized based on the series of frames given to the model, ACT sends alerts to all assigned endpoints.

The module supports real-time multiple stream processing as well as offline analysis of video recordings.

The models are trained on a large amount of anomalous and normal videos. This allows ACT to operate in versatile environments and scenarios to immediately react and send alerts in case of an anomaly.

The system continuously self-learns, that’s why it can be adjusted specifically for your case, if the current dataset is not fully capturing the peculiarities of the environment at your premises.

How It Works

Scylla is optimized to work on multiple video streams using a single GPU and provide real-time event tracking.

Once an anomalous event has been recognized based on the series of frames given to the model, Scylla sends alerts to all assigned endpoints.

The module supports real-time multiple stream processing as well as offline analysis of video recordings.

The models are trained on a large amount of anomalous and normal videos. This allows Scylla to operate in versatile environments and scenarios to immediately react and send alerts in case of an anomaly.

The system continuously self-learns, that’s why it can be adjusted specifically for your case, if the current dataset is not fully capturing the peculiarities of the environment at your premises.

AI detects

Fighting

Abnormal shopping behavior

Slip & fall

Scylla AI detects

Fighting

Abnormal shopping behavior

Slip & fall

What makes ACT Behavior Recognition & Anomaly Detection System stand out

Real-time detection of fighting and anomalous consumer behavior that may result in shoplifting

Detection of environmental anomalies, such as smoke and fire

Centralized solution capable of handling multiple camera streams simultaneously

Flexible deployment based on the customer’s choice - can be on-site, cloud-hosted or hybrid

What makes Scylla Behavior Recognition & Anomaly Detection System stand out

Real-time detection of fighting and anomalous consumer behavior that may result in shoplifting

Detection of environmental anomalies, such as smoke and fire

Centralized solution capable of handling multiple camera streams simultaneously

Flexible deployment based on the customer’s choice - can be on-site, cloud-hosted or hybrid

FAQ

What is Anomaly Detection and Behavior Recognition used for?

There are 3 submodules of ACT Anomaly Detection and Behavior Recognition system each one of which is designed to detect a specific event, such as fight and violence detection module, smoke and fire detection module, and potential shoplifting detection module. All three ACT Anomaly Detection and Behavior Recognition submodules analyse such events from CCTV video footage either in real time or forensically, from video databases. When a specific event is detected, the system initiates a corresponding alert and distributes it through predefined alerting pathways to the end user.

How are anomalies detected?

A sequence of frames is provided to the pre-trained neural network engine of ACT Anomaly Detection and Behavior Recognition. Thus this 3D matrix (2D frames + time) is considered as an input. ACT Anomaly Detection and Behavior Recognition AI then decides if the actions in this matrix correspond to the action sought after and triggers an alert if the probability is above the defined threshold.

What is considered an anomaly?

The anomalies detected by ACT Anomaly Detection and Behavior Recognition are based on the training set. In particular, the fight detection model is trained on a large real-world dataset of fights and assault cases recorded from CCTV cameras. Thus the anomaly it detects will include acts of violence including fighting and wrestling. Similarly, the smoke & fire detection submodule of ACT Anomaly Detection and Behavior Recognition is triggered when these hazardous events are detected in the scenery.

What is the minimum time for the system to recognize an event as an anomaly?

The system accumulates a number of consecutive frames and analyses the whole batch as a unit. The duration of this batch is different for different submodules but on average the chunk duration is 3-5 seconds.

What is the maximum distance for effective anomaly detection and behavior recognition?

The maximum distance will depend on the camera characteristics. More specifically, on the lens. Typically, for proper illumination (400 lx and higher) the requirement is that the person height should take up 1/6th of the frame height. For most cameras this results in maximal detection distances of up to 15 meters. If optical or digital zoom is used or the camera does not have standard aperture/focal range, the maximum distance can vary.

Can it be integrated into an existing CCTV network?

Absolutely. After all, what ACT Anomaly Detection and Behavior Recognition needs is the video feed from CCTV which is provided by most CCTV networks and video management systems. Moreover, ACT Anomaly Detection and Behavior Recognition can be two-way integrated with major VMS providers, such as Milestone, Genetec, NetworkOptix, and others.

How does abnormal shopping behavior detection work?

The abnormal shopping behavior detection model is trained on a large dataset of videos from surveillance cameras, where shoplifting events occur. The submodule is designed to detect an action of taking an item and trying to conceal it. The system is intended to analyze the streams coming from the retail environment excluding the cashier area, since after paying for an item a customer could take actions that are identical to concealing goods. Please note that since shoplifting itself is a subtle event to accurately detect with a high probability, ACT monitors suspicious behavior that can result in shoplifting.

Can shoplifting be detected when the face is covered?

Yes. The alert is triggered based on the actions in the camera view. Facial biometrics plays no role in the decision making process of AI.

How does smoke and fire detection work?

The Smoke and Fire detection submodule is built on the largest dataset for the Anomaly Detection and Behavior Recognition models to date. The system alerts in the event of either smoke or fire. The system can be installed in both indoor and outdoor environments.. As the question suggests, the system alerts in the event of either smoke or fire. The environment where the system could be installed can be both indoors and outdoors.

How can the Behavior Detection System help your security team?

ACT Anomaly Detection and Behavior Recognition is designed to help security units by supporting their daily operations, augmenting their capabilities and eliminating possible human-factor related flaws. Also, in case of a possible threat the alert that is sent out by ACT is enriched with information crucial for quick and inclusive analysis of the threat on site and effective planning of dedicated counteractions.

What does the system do after detection?

An alert containing all the crucial information is compiled and delivered to end users responsible for security. There are several customizable alerting pathways including: dashboard, mobile alerting application, access point relay boards, and VMS alerting API.

Can Anomaly Detection work on the cloud?

Yes, Anomaly Detection and Behavior Recognition can work both on cloud and on premise.

How many fight instances can a single camera detect?

ACT Anomaly Detection and Behavior Recognition treats the whole frame and analyses all actions within the frame. Thus, regardless of the number of fighting instances in the frame – the alert will be triggered if there are any instances of violence.

How does the system understand whether it is a fight, an act of vandalism or shoplifting?

The acts of fights and vandalism are detected by a dedicated model that was trained on a large amount of real-world video recordings from CCTV cameras. The model for shoplifting is separate and it is trained to detect possible shoplifting actions only.

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