Intelligent video analytics software development

Analyze your camera footage automatically for real-time action and insights, creating a smart and secure environment
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Artificial Intelligence for video monitoring

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 gives early threat warnings, real-time alerts, and detects objects, people, or specific behaviors. It extracts valuable information to organize your video data for analysis, all without manual monitoring or the need for expensive new equipment.

AI video analysis software leverages Computer Vision and Deep Learning technologies to automatically process visual data, e. g. surveillance footage, 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.

Artificial Intelligence for video monitoring
Intelligent Video Analytics - how it works. Intelligent Video Analytics Software Development expertise page.

Cut the costs by eliminating manual video monitoring

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Our expertise in intelligent video analytics

Our expertise in intelligent video analytics

With over 17 years of experience in Computer Vision, we’ve provided modular video analytics software solutions. Our solutions cut costs by eliminating manual video monitoring while maintaining the highest accuracy in video analysis.


Our AI video analytics software services

  • Object, activity and face detection – identifying and tracking objects, actions, and faces in a video. Using Computer Vision, the software analyzes frames to enhance security and surveillance applications.
  • Vehicle identification – entails recognizing and tracking vehicles within a video feed. This software identifies and monitors vehicles for applications like traffic management and parking solutions.
  • Violence / Action detection – involves recognizing aggressive or unusual activities within a video stream. The software identifies potential instances of violence or specific actions, aiding in security and public safety applications.
  • Object counting – automatically determining and tallying the number of specific objects within videos. This technology accurately counts objects, contributing to applications like crowd management, inventory control, and traffic monitoring.

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. Video analytics software solves this task by accelerating video management across diverse industries and use cases.

Every single detail is noticed

Every single detail is noticed

Video analytics software provides continuous and unflagging attention, ensuring nothing is overlooked.

24/7 uninterrupted monitoring

24/7 uninterrupted monitoring

Video analytics software accelerates video management processes. Unlike human monitoring, it doesn’t suffer from fatigue, allowing it to process and analyze video footage continuously without breaks, contributing to real-time insights and decision-making.

Optimized resource utilization

Optimized resource utilization

Video Analytics software optimizes resource utilization by automating tasks, reducing the need for manual oversight, and improving operational efficiency, resulting in cost savings and increased productivity.

Computer Vision implementation domains

Healthcare

  • Enhanced fundus images &  registration
  • Pupil & eyelid tracking (eye-surgery aid)
  • Cell classification via morphology, texture, and intensity features
  • Microscopy image enhancement
  • Wearables for the visually impaired

Retail

  • Automated checkout for cashierless retail
  • Product ID for vending & fridges
  • Body measurement for virtual fitting
  • Photo-based sizing for apparel design
  • Counterfeit product detection & brand verification

Security

  • Face detection and recognition in images and videos
  • Vehicle  license plate recognition
  • Violence detection
  • People & motion detection
  • Fall detection
  • Driver activity & fatigue recognition

Transport

  • Traffic flow measurement
  • Vehicle detection and classification
  • Bike & helmet detection
  • Monocular visual odometry

Fintech

  • Data extraction for financial document processing
  • Template ID for forms
  • OCR for handwritten finance
  • Supplier search for e-procurement & e-sourcing
  • Text recognition for claim processing

Abto’s video analytics applications’ across domains

Public safety

Public safety

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

Manufacturing

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

Retail

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

Aerial inspections

Aerial inspections

– Agricultural inspections
– Manufacturing & industrial inspections

Smart homes

Smart homes

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

Intelligent transportation & ADAS

Intelligent transportation & ADAS

– Traffic flow monitoring: vehicle tracking & counting, illegal turns / wrong way movement detection
– Helmet use analysis for cyclists and motorcyclists
– Driver monitoring: analysis of driver’s focus and detection of fatigue, recognition of driver’s actions

AI-based pose detection for MSK rehabilitation

Abto Software delivers the technology for real-time markerless motion capture that ensures skeleton tracking and high-quality human motion recognition that can be applied for a wide range of movements and exercises using just cameras of mobile devices or PC.

Business value of markerless pose analysis:

  • 150% ROI
  • 5 hours saved by therapists per week
  • 27% faster patients recovery
  • 1.6 times more patients
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AI-driven fall detection module for video analytics platform

After detecting all of the people in the input video stream and assessing their key points the system classifies each person whether they have or have not fallen down.
The latter comprises the next options: person sitting on the floor, person sitting on other surface, and person standing. If at least one person have fallen down the fall detection alarm is triggered.

Fall detection module business value

  • Continuous fall detection with instant alerts – real-time reporting of slip and fall incidents with uninterrupted 24/7 system operation
  • Efficient data visualization and integration – accidents are logged in a database and displayed on a web-accessible dashboard, providing administrators with an easily configurable overview of safety status. Data can seamlessly integrate with third-party systems via API.
  • GDPR-Compliant Solution – our fall detection system ensures privacy compliance, avoiding facial recognition or personal data collection, aligning fully with GDPR regulations.
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Automatic fruit counting for conveyor systems

Camera-based solution for automated fruit counting in processing plants, offering efficiency for growers, packers, and machinery providers

Business value of implementing AI-driven conveyor system:

  • Real-time production reporting for enterprise-level software
  • High product counting accuracy of 99.5% even with varying illumination and different products placement
  • Universal counting algorithm
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AI & Computer Vision technology stack and approaches

In video analytics software development, we use cutting-edge technologies to tackle intricate video analysis challenges with the highest accuracy and processing speed. Our R&D engineers stay abreast of the latest advances in Computer Vision, exploring innovations in advanced video processing, Deep Learning, and Artificial Intelligence.

Models and approaches
  • Convolutional Neural Networks (CNN): Two-stream CNN, Mask R-CNN, ResNet, SqueezeNet, Inception v1-v4, Inception ResNet, EfficientNet, SSD, U-Net, DensePose, OpenPose, FCN, DeepLab
  • Recurrent Neural Networks (RNN):  LSTM, GRU
  • Transformers, Attention mechanism
  • Generative models and algorithms: GAN, Genetic Algorithms, Autoencoders and AutoRegressive
  • Networks: Autoencoders, AutoRegressive networks
  • Few shot learning (classification, object detection)
  • Traditional ML algorithms: SVM, Bag of Words, K-means, DBSCAN, ORB, SIFT, Haar cascades, DecisionTree, RandomForest, KNN
  • CV techniques: SFM, SLAM, Visual odometry
  • Synthetic data generation
Frameworks & libraries
  • Development Environments: MATLAB, Simulink, RStudio, LabView, PyCharm, SPYDER, Jupyterlab/Jupyter notebooks
  • ML and Deep Learning libraries: TensorFlow, Skflow, PyTorch, NumPy, SciPy, Scikit-learn, Pandas
  • CV libraries: OpenCV, Dlib, BoofCV, Google ML Kit, CoreML, Apple Vision
  • Others: CUDA, SimpleCV, GPUImage, DeepFace, Tesseract, OCRopus
  • ChatGPT
Programming languages
  • Python
  • C++
  • Java/Android
  • Objective-C
  • MATLAB/Octave
  • R
  • SQL Server
  • Convolutional Neural Networks (CNN): Two-stream CNN, Mask R-CNN, ResNet, SqueezeNet, Inception v1-v4, Inception ResNet, EfficientNet, SSD, U-Net, DensePose, OpenPose, FCN, DeepLab
  • Recurrent Neural Networks (RNN):  LSTM, GRU
  • Transformers, Attention mechanism
  • Generative models and algorithms: GAN, Genetic Algorithms, Autoencoders and AutoRegressive
  • Networks: Autoencoders, AutoRegressive networks
  • Few shot learning (classification, object detection)
  • Traditional ML algorithms: SVM, Bag of Words, K-means, DBSCAN, ORB, SIFT, Haar cascades, DecisionTree, RandomForest, KNN
  • CV techniques: SFM, SLAM, Visual odometry
  • Synthetic data generation
  • Development Environments: MATLAB, Simulink, RStudio, LabView, PyCharm, SPYDER, Jupyterlab/Jupyter notebooks
  • ML and Deep Learning libraries: TensorFlow, Skflow, PyTorch, NumPy, SciPy, Scikit-learn, Pandas
  • CV libraries: OpenCV, Dlib, BoofCV, Google ML Kit, CoreML, Apple Vision