Video annotation involves detecting objects and events within video content and labeling them with specific markup using advanced video labeling tools. These labels are then utilized by machine learning algorithms to build models that extract meaningful insights.
5+
Years on the market
1000+
Successfully implemented projects
1000+
Independent Annotators
24/7
Support Availability
90%
hold BS, MS, or PhD in Math/Computer Science
Key Features of our Video Annotation Services
Utilize annotated video frames as training data to detect objects and track human poses
#1
Accurate Training Data with Annotated Video Frames
Our advanced video annotation and labeling services deliver high-quality annotated video frames that serve as precise training data for deep learning and machine learning models. Leveraging state-of-the-art tools and techniques, we help you build computer vision models that excel in object detection and tracking.
#2
Enhance Autonomous Vehicles with Video Annotation
Our video annotation solutions are critical for self-driving vehicle development. We annotate videos frame-by-frame to help autonomous systems identify vehicles, traffic signals, sign boards, street lights, lanes, cyclists, and pedestrians. These detailed annotations form the ground truth data essential for creating reliable and fully functional autonomous vehicle models.
#3
Improve Human Activity Recognition and Pose Estimation
By accurately annotating human poses, our video annotation services enable machines to detect and track human activity in various environments. Our expert team uses live video annotation and cutting-edge techniques to capture facial expressions and body movements, ensuring your AI systems can effectively understand and analyze human interactions.
Advanced Video Annotation Technology
We provide accurate and cost-effective video annotation solutions to streamline your business processes. Here’s a brief overview of our services:
2D Bounding Boxes
Draw rectangular boxes around objects in each video frame to accurately identify and categorize people or items.
3D Cuboid Annotation
Convert 2D video frames into a 3D perspective by drawing bounding boxes that outline objects, enhancing visual perception for AI models.
3D Point Cloud Annotation
Analyze 3D scenes to detect objects in space and track motion patterns, supporting advanced applications in machine learning and computer vision.
Landmark Annotation
Enable precise facial recognition by marking key facial features, ensuring detailed analysis for human-centric AI tasks.
Lines & Splines
Identify and track the starting and ending points of lines or curves, monitoring changes in direction, speed, and shape over time.
Polygons Annotation
Draw polygons around objects such as vehicles, people, and buildings to segment images and video content accurately.
Events Classification
Manually label video clips with tags related to specific events by drawing bounding boxes around objects, improving event detection accuracy.
Event Tracking
Develop an event tracking system that provides valuable insights into user behavior, such as monitoring the frequency of visits to particular locations.
Use Cases
Our comprehensive video annotation and labeling services empower various industries - from automotive and retail to e-commerce - with high-quality AI training data.
Security
Enhance surveillance systems by accurately detecting humans, vehicles, animals, and real-estate properties using advanced AI and video annotation techniques.
Self-Driving
Accelerate the deployment of autonomous vehicles with precise video annotation that provides robust training data for AI-driven navigation and object detection.
Healthcare
Improve diagnostic accuracy by automating disease detection through expertly annotated videos, streamlining AI and ML processes in medical applications.
Media
Boost content quality by integrating annotated training data for improved audio and video conversions, enhancing reporting and interview analysis.
Manufacturing
Optimize workflows and decision-making in manufacturing with high-quality AI training data derived from detailed video annotation, supporting efficient process automation.
Sports
Leverage AI to analyze athlete performance and strategize game plans, using annotated video data to monitor movements and enhance training outcomes.
FAQs
For startups and SMBs, outsourcing video annotation is typically recommended. Outsourcing saves time and money while ensuring higher accuracy, whereas in-house annotation can be labor-intensive and slow.
A robust video annotation tool provides features such as precise timestamp annotation, shape markup, screen recording, frame-accurate feedback, and hassle-free sharing, all of which enhance collaboration and accuracy.
1. Dataset quality: Start with a clean dataset by removing low-quality and duplicate data before annotation.
2. Appropriate Labeling: Use the right labels (e.g., bounding boxes for object detection) to ensure data is ready for machine learning.
3. Organized Labels: Implement customized label structures and accurate metadata to avoid miss-classification.
4. interpolation and keyframes: Interpolation & Keyframes: Use keyframes and interpolation to reduce manual work on predictable motion segments, speeding up the process while maintaining quality.
5. User-friendly Tools: Choose robust, efficient annotation tools to create precise labels that improve training outcomes.
Video data is complex and high-dimensional, making it challenging for computer vision algorithms to accurately detect and label objects and events. Additionally, the dynamic and intricate nature of video content often requires human oversight to achieve a comprehensive understanding.
Interested in Joining Our Team?
In today’s tech-driven landscape, building a career in Artificial Intelligence (AI) is both exciting and rewarding. Become an Annotation Specialist with us and help craft high-quality training datasets that power innovative AI solutions.
Get in Touch with us
Vietnam Office
102 Tran Phu, Mo Lao, Ha Dong, Ha Noi
Give Us A Call
+84 812-436-221
