UVAP
  • Key Features
  • Feature Demos
  • Installation
  • Developer Guide
  • Operation Guide
  • Tutorials
  • Help

UVAPUltinous Video Analytics Platform

Ultinous Video Analytics Platform (UVAP) is a set of software services that can be composed and extended in a flexible way to build scalable, distributed video processing applications in multiple domains such as retail, security or elderly care.

Overview

  • Introduction
  • Changelog

Key Features

  • Features Overview
  • Person Detection
    • Head Detection
    • Anonymization
    • 3D Head Pose Detection
    • Skeleton Detection
    • Detection Filtering
  • Movement Detection
    • Person Tracking
    • Pass Detection
  • Facial Properties and Recognition
    • Gender Detection
    • Age Detection
    • Face Mask Detection
    • Feature Vector Extraction
    • Feature Vector Clustering
    • Reidentification
  • Configuration
    • Stream Configuration
  • Image and Video
    • Frame Info
    • Resizing and Cropping Images
    • Image Streaming
    • Video Annotation
    • Saving Video Streams

Feature Demos

  • Starting Feature Demos
  • Person Detection
    • Head Detection
    • Anonymization
    • 3D Head Pose Detection
    • Skeleton Detection
    • Detection Filtering
  • Movement Detection
    • Tracking
    • Pass Detection
  • Facial Properties and Recognition
    • Demography (Age and Gender)
    • Face Mask
    • Single Camera Reidentification Demo with Pre-clustering
    • Reidentification Demo with Person Names
  • Image and Video
    • Show Image
    • Saving Video Streams
  • Practice Use Cases

Installation

  • System Requirements
    • Hardware Requirements
    • Software Requirements
  • License Key
  • Setting Up UVAP
    • Creating UVAP User
    • Installing NVIDIA Video Driver
    • Adding Docker Environment
    • Starting Kafka
    • Downloading Helper Scripts
    • Installing UVAP
    • Additional tools
  • Upgrading UVAP

Developer Guide

  • Architecture
  • Data Model
  • Microservice Descriptions
    • Multi Graph Runner
    • Detection Filter
    • Tracker
    • Pass Detector
    • Feature Vector Clustering
    • Reidentifier
    • Video Capture
  • Microservice Configuration
    • Microservice Superconfiguration
    • Configuring Multi-Graph Runner
    • Configuring Detection Filter
    • Configuring Tracker
    • Configuring Pass Detector
    • Configuring Feature Vector Clustering
    • Configuring Reidentifier
    • Configuring Video Capture
  • Tools
    • Stream Configuration UI
  • Extending UVAP

Operation Guide

  • UVAP Operation Guide
  • Microservice Operation
    • Generic Operation Guide
    • Operating the Multi-Graph Runner

Tutorials

  • Example Analysis Results
  • Video Annotation Tutorial

Help

  • UVAP License Terms
  • Support
  • UVAP Training
  • Typographic Conventions
  • Glossary
  • Trademark Information
  • GitHub

Introduction

Ultinous Video Analytics Platform (UVAP) is a set of software services that can be composed and extended in a flexible way to build scalable, distributed video processing applications in multiple domains such as retail, security or elderly care.

Video Analysis Capabilities

UVAP provides a rich set of deep-learning-based advanced video analysis models. These models are industry leading in accuracy along with efficient processing. The available core models are the following:

  • Head/face detection
  • 3D head pose
  • Face recognition, re-identification
  • Full body re-identification
  • Age
  • Gender
  • Human body pose
  • Tracking
  • Pass detection, counting

Example Use Cases

UVAP has been used to solve real world problems in different domains. For example:

  • Queue management system for retail stores. Customers are counted at the doors and in the queuing area in real-time. A prediction model can tell if there will be a queue in the next few minutes and staff is alerted before it happens.

  • Fall detection in elderly care homes. The system uses two 3D-calibrated cameras per room and runs human body pose estimation. Based on the body pose, fallen body pose can be recognized. An alert is sent to the staff in real-time. Staff personals can look at the alert, validate the images and decide to take action.

  • Measure waiting time on airports. Face recognition is applied at the entrance and exit points in real-time to measure actual waiting time. Prediction is applied and displayed to customers entering the queue.

  • Recognize unsafe escalator usage. Based on head detection, tracking and full body pose, different unsafe situations are recognized. Such as: wrong direction, leaning out, crowd

Help
UVAP License TermsGlossaryTypographic ConventionsTrademark InformationSupport
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