Live Video Stream Annotation for Traffic Management and Road Planning

The Company: An Integrated Data Analytics Company

Industry: Data Analytics

Company Headquarters: San José, CA, USA

Annotation of Live Video Streams for Traffic Management and Road Planning

Request for Information

If you’d like to get more information about the case study and pricing, please contact our experts today.

Get in Touch →

The Objective:

To assist government in utilizing traffic camera feeds, both live and recorded, to analyze traffic flow, assess congestion, and optimize lane management, the client wanted to categorize and label thousands of vehicles based on movement patterns and approach directions. These labeled images were crucial for training their machine learning models aimed to enhance traffic management through advanced technology development.

The Challenges:

High-Volume Data Handling - Deploying an annotation system capable of processing large volumes of video data with minimal delay to ensure real-time monitoring.
Scalability and Performance - Managing an increasing number of video feeds and simultaneous annotations while maintaining high performance and accuracy.
Skilled Annotator Training - Training a team of skilled annotators to effectively handle varying conditions such as camera quality, lighting, occlusions, and complex traffic scenarios.
Effective Tracking Mechanism - Building a robust tracking mechanism to maintain continuity and accuracy in annotations.
Consistent Annotation Guidelines - Developing comprehensive annotation guidelines and ensuring consistency across different annotators.
Data Privacy and Security - Implementing strong data privacy and security measures, including encryption, access controls, and anonymization techniques, to comply with regulations.
Low-Latency Network Infrastructure - Establishing a robust, low-latency network infrastructure to efficiently transmit video feeds and avoid delays in real-time annotation.
System Compatibility and Data Transfer - Ensuring compatibility and seamless data transfer between different systems to provide accurate traffic management insights.
Adverse Condition Management - Accurately annotating images captured under extreme weather conditions, heavy congestion, and diverse vehicle types.

HabileData’s Solution

Approach

HabileData established a comprehensive and structured workflow for video annotation, encompassing task assignment, quality control, and review processes. This workflow facilitated efficient collaboration among annotation teams and ensured the maintenance of high-quality standards.

An initial assessment of vehicle and pedestrian images in pre-recorded traffic videos and live video streams was conducted to expedite the labeling process.

Input Data

Video footage was provided as pre-recorded videos and URLs to live video streams.
Pre-recorded videos were systematically uploaded to OneDrive, organized by city.
For live video streams, human annotators securely accessed the City’s traffic camera network via VPN using pre-provided credentials.

Labeling and Segmentation

Vehicles were labeled by category, including model name, color, and direction.
Objects were classified into 14 categories: Car, SUV, small truck, medium truck, large truck, pedestrian, bus, van, group of people, bicycle, motorcycle, traffic signal green, traffic signal yellow, and traffic signal red.
Vehicles were tagged and segmented based on turning movement or direction of approach.
Obstructed vehicles were excluded from labeling.
Ambiguities due to poor lighting or weather conditions were re-validated by the client.

Annotation Technique

A line-based technique was employed to uniquely count vehicles and other objects.
The state of the line changed from unoccupied to occupied and then back to unoccupied, incrementing the count.
A red demarcation line was used to identify small vehicles that were not labeled.

Audit and Review

A team of senior auditors reviewed approximately 10% of the annotated images.
Anomalies or deviations in the data were used for further training purposes.
Erroneous annotations were flagged for re-labeling.

Deliverables

City-wise segregation enabled the efficient uploading of labeled images to OneDrive.
A detailed report was generated, listing the number and types of vehicles annotated for record-keeping purposes.

Business Impact

Enhanced traffic management
Improved safety and incident response
Increased operational efficiency

Value Addition

Annotating vehicles in pre-recorded and live video streams enhanced traffic management capabilities, leading to more efficient traffic flow and improved overall urban mobility.

Talk with our expert team who can help you with all your queries.

Get a Quote

Annotation of Live Video Streams for Traffic Management and Road Planning