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Intelligent Video Analytics Software Development

Automatically analyze video from your existing camera network to take action in real-time and unlock insights to create a smart, safe environment.

Manual video monitoring is a daunting task: it is labor-intensive, costly, and mostly ineffective. Abto Software helps you to upgrade your existing camera and monitoring systems with custom AI-based video analytics modules. Our video analytics software facilitates early threat warnings with real-time alerts, detect objects, people or specific behaviours and extract other valuable information to structure your video data for further analysis, all without manual monitoring or the need to install new costly equipment.

Intelligent Video Analytics software leverages Computer Vision and Deep Learning technologies to automatically process visual data, e. g. surveillance footages, security videos or aerial imagery, and differentiate between objects, people, conditions, and events in real time. This information is used to provide advanced warnings in forms of e-mails, notifications or direct police/ambulance calls. Aggregated over time, intelligent video analytics software helps to uncover insights invaluable for ensuring personal and public safety.

We deliver Video Analytics solutions for multi-billion corporations.

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Intelligent video analytics software development

Our Expertise in Intelligent Video Analytics

With more than 8 years of experience in Computer Vision domain, we have delivered a number of modular video analytics software solutions that helped our customers cut costs with eliminating manual video monitoring while sustaining the highest accuracy of video analysis.

Our Intelligent Video Analytics Services

Object Recognition and Tracking

Facial Recognition and Emotion Analysis

Activity Recognition

Violence and Fight Detection

Personal Protective Equipment (PPE) Detection

Aerial Imagery & Video Processing

How Intelligent Video Analytics Software Addresses Video Management Challenges

Humans lose from 50% to 90% of their visual perceptibility after 20 minutes of continuous video monitoring. Today this task is solved by Video Analytics software implementation that accelerates video management across many industries for various use cases.

Public Safety

  • Person identification: facial recognition, suspect search
  • Gun & knife detection
  • Violence detection
  • Loitering & kidnapping detection
  • Crowd management for accident prevention

Intelligent Transportation & ADAS

  • Traffic flow monitoring: vehicle tracking & counting, illegal turns / wrong way movement detection
  • Helmet use analysis for cyclists and motorcyclists
  • Driver monitoring: driver’s attention analysis and drowsiness detection, driver activity recognition

Manufacturing

  • PPE (personal protective equipment) compliance inspection: helmet, vest, goggles, boots, coat detection
  • Trip, slip, and fall detection
  • Automated worker check-in with facial recognition

Smart Homes

  • Motion detection: intrusion and theft detection
  • Fire and smoke detection
  • Gesture command recognition

Aerial Inspections

  • Agricultural inspections
  • Manufacturing & industrial inspections

Retail

  • Visitor counting and people flow analysis with heatmaps and pathmaps
  • MAG (mood / age / gender) analysis
  • Eye & gaze tracking for attention analysis
  • Planogram compliance verification
Use case

Fall Detection Module for Video Analytics Platform

Our Computer Vision engineers have developed a video analytics module that manages slip and fall accidents in real-time. The delivered video analytics software generates an alert when someone falls down within the monitored area and sends the alert together with the video feed to the designated person – it can be an elderly caretaker, a police officer, a security staff member or a location administrator.

Employing Deep Learning models together with advanced image processing techniques allowed us to reach 95%+ accident detection accuracy while maintaining real-time video stream processing.

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Business Value

24/7 Video Processing with Real-time Alerts

Slip and fall accidents are reported in real-time while the system works continuously without disruption or downtime.

Data Visualization and 3rd Party Integration

Each accident is displayed on the web-accessible dashboard that gives administrators at a glance awareness of the current safety status in the facility. This information can be automatically exported to the 3rd party reporting or data management systems via API or other methods.

GDPR Compliance

The fall detection system does not utilize way facial recognition or person identification technologies. It does not collect any sensitive or personal data and is fully GDPR compliant.

Areas of Applications

Health Facilities

Both patients and caregivers are vulnerable to falling on hospital premises. Early fall detection ensures quick response and minimizes the negative outcome of the accident.

Retail

Fake slip and fall claims cause shopping malls substantial financial losses. Collecting video evidence through camera-based fall detection is the most effective way of preventing fraudulent insurance payouts.

Construction & Manufacturing

Slip, trip, and fall accidents account for 28% of all fatal occupational injuries in construction and manufacturing. With an automatic fall detection system, employers can identify and eliminate fall hazards.

Fall Detection Module for Video Analytics Platform

Computer Vision & AI Expertise

For video analytics software development, we employ state-of-the-art technologies to solve the most complex video analysis challenges with the highest accuracy and processing speed. Our R&D engineers constantly analyze the latest advancements in Computer Vision to stay up to date with the recent innovations in the fields of advanced video processing, Deep Learning, and Artificial Intelligence.

Frameworks & Libraries

  • OpenCV v3-v4
  • TensorFlow, PyTorch, Keras
  • NumPy, Scikit-learn, Pandas
  • Dlib, BoofCV
  • Mobile SDKs: Google ML Kit, CoreML, Apple Vision

Models & Approaches

  • Deep Learning & Neural Networks: CNN, Two-stream CNN, RNN, Mask R-CNN, ResNet, SqueezeNet
  • Inception v1-v4, Inception ResNet
  • LSTM, GRU
  • Detectron
  • Darknet
  • YOLO v1-v4, Tiny YOLO
  • Pose Estimation: DensePose, OpenPose
  • GAN
  • Genetic Algorithms
  • Synthetic data generation
  • SVM, Bag of Words, K-means, ORB, SIFT, Haar cascades

Programming Languages

  • Python
  • C++
  • Java/Android
  • Objective-C
  • MATLAB/Octave
  • R

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