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USE CASE

Object Tracking Annotation

Datasets for solving video analytics tasks
Computer Vision Ability of a machine to interpret, analyze, and understand visual data
Classification Process of recognition and grouping of objects into preset categories
Object Detection Process of locating instances of objects with Bounding Box
Smart City The use of machine learning for creating Automated and Efficient Urban Development

Our Partners

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CASE DESCRIPTION

Tracking people on the streets

  • 20,000 frames
  • 4 weeks

Tracking each person in the frame by Bounding-Box markup using CVAT. The labeling is presented in the form of coordinates in XML format

APPLICATION AREAS

– Tracking the movement of people to analyze flows in commercial spaces in order to optimize the placement of goods

– Recognition of suspicious human behavior to alert security services and prevent crimes

– Crowd density assessment for monitoring at public events to ensure safety

– Tracking and automated counting of people to assess visitors to public spaces

– Tracking of workers at production to ensure labor safety and compliance with local regulations

Tracking a basketball

  • 10,000 frames
  • 2 weeks

Ball detection using Bounding-Box. Classification by overlap and position of the ball in CVAT. The labeling is presented in the form of coordinates and attributes in XML format

APPLICATION AREAS

– Ball tracking to monitor game statistics and analyze team performance

– Classification of ball position to determine the strengths and weaknesses of the team and individual players

– Ball tracking to predict game results and player statistics

– Ball tracking to help analyze players’ performance and help improve their skills

– Tracking to create statistical reports that can be used by coaches and team managers to make decisions

– Tracking and classification of ball position for use in training for children and beginning players to help them develop and improve their skills

Tracking cars on video

  • 20,000 frames
  • 4 weeks

Tracking each car in the frame using Bounding-Box. Classification of cars depending on the type of body. The labeling is presented in the form of coordinates and attributes in XML format

APPLICATION AREAS

– Identification and tracking of vehicle speed to ensure safety on the highways

– Traffic tracking and counting to monitor road congestion in real time

– Classification of vehicles by body type for traffic analysis of urban infrastructure

– Recognition of abnormal vehicle behavior to alert security services in real time

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Why
Training Data

  • Quality Assurance:
  • Enhanced Data Accuracy
  • Consistency in Labels
  • Reliable Ground Truth
  • Mitigation of Annotation Biases
  • Cost and Time Efficiency
  • Data Security and Confidentiality:
  • GDPR Compliance
  • Non-disclosure agreement
  • Data Encryption
  • Multiple data storage options
  • Access Controls and Authentication
  • Expert Team:
  • 6 years in industry
  • 35 top project managers
  • 40+ languages
  • 100+ countries
  • 250k+ assessors
  • Flexible and Scalable Solutions:
  • 24/7 availability of customer service
  • 100% post payment
  • $550 minimum check
  • Variable Workload
  • Customized Solutions

Team leads project

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Sergey Razumny
TeamLead Crowd Solutions
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Arthur Kazukevich
Python-developer
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Wadim Starosotnikow
Senior quality control manager
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