Video Annotation Services

iMerit delivers stellar video annotation services that power AI, machine learning, and data operation strategies.


Bounding box annotation of cars, for Autonomous Vehicle applications

What is Video Annotation?

Video annotation is the process of labeling or tagging video clips which are used for training computer vision models to detect or identify objects. Unlike image annotation, video annotation involves annotating objects on a frame-by-frame basis to make them recognizable for machine learning models.

High-quality video annotation generates ground truth datasets for optimal machine learning functionality. There are numerous deep learning applications for video annotation across industries including self-driving cars, medical AI, and geospatial technology.

What are the types of video annotation services?

iMerit provides video annotation services for all annotation projects including bounding box annotation, polygon annotation, keypoint annotation, and semantic segmentation. iMerit’s team works with the client to calibrate the quality and throughput of the job and deliver the best cost-quality ratio as you iterate. We recommend running a sample batch to clarify instructions, edge cases, and approximate task times, before launching full batches.

iMerit’s video Annotation Services

Bounding Box annotation for detection and tracking of object, AI in Government application
Bounding Boxes

It is the most commonly used type of video annotation in computer vision. iMerit computer vision experts use rectangular box annotation to illustrate objects and create training data so apps and algorithms can identify and localize objects during ML processes.

Polygon annotation where each vertex of a target object is labeled, regardless of shape, for geospatial applications
Polygon Annotation

Expert annotators plot points on each vertex of the target object. Polygon annotation allows all of the object’s exact edges to be annotated, regardless of shape.

Semantic segmentation to classify each pixel of a car, use case of computer vision
Semantic segmentation

Videos are segmented into component parts, by the iMerit team, and then annotated. iMerit computer vision experts examine video frames and classify objects pixel by pixel.

Point annotation for locating an object its component parts in an image, for Geospatial applications
Keypoint annotation

iMerit teams outline objects and shape variations by connecting individual points across objects. This annotation type detects body features and could include facial expressions and emotions.

Landmark annotation
Landmark annotation

iMerit experts use points on landmarks and peoples’ faces when annotating video footage. Expertly-conducted landmark annotation creates valuable training datasets for high-performing computer vision models.

3d cuboid annotation
3d cuboid annotation

iMerit experts perform object tracking by drawing cubes around objects. This allows systems to recognize a given object’s length, width, and height.

Polyline annotation
Polyline annotation

iMerit experts create training datasets using polyline annotation that teach models to identify physical boundaries to operate within.

Rapid annotation
Rapid annotation

iMerit’s video annotation platform utilizes video interpolation to rapidly annotate suitable video footage. iMerit annotation experts create best-in-class video training datasets in rapid time for any AI or ML project.

Video annotation

Expert Consultation

Transformative, solution-based approach. Interdisciplinary video annotation problem solving. Agility and responsiveness, time-to-value enhancers.


Targeted resources. Custom skilling. Focused and deep microlearning curriculum. Domain expertise. Rostering tools.

Workflow Customization

Alignment of video annotation tools and processes. Structured Development Milestones. Two-step production and QA annotation workflows.

Feedback Cycle

Transparency via analytics. Real time monitoring and service delivery insights. Edge case Insights. Dynamic model improvement.


Assessment of deliverable. Appraisal of key metrics, quality control processes. Model reconsideration. Analysis of business outcome.

Video Annotation use cases


Semantic video annotation of surveillance images

iMerit’s video annotation experts have processed 500+ video datasets of various formats at a much higher level of detail than the client’s own teams. Our expert annotators solved the challenge of frame-by-frame manual processing of CCTV videos by accurately identifying and annotating required objects.

Moving bounding boxes using video annotation

iMerit’s video annotation experts created datasets to train the world’s most advanced machine learning solutions for rearview cameras and alert systems. Our experts annotated still and moving objects using bounding boxes in video material to identify potentially dangerous objects.

Detecting operating boundaries with polyline annotation

Detecting operating boundaries with polyline annotation

iMerit experts will comb through an entire video using the iMerit proprietary annotation platform to teach a vehicle to accurately detect street lanes, road markings, directions, divergence, and traffic.

Facial recognition using keypoint annotation

iMerit experts used video editing to pause and apply keypoints on a person’s face. This allowed iMerit to create world-class training datasets for use in facial recognition models. This advanced technology is helping in public areas where crimes occur to identity and apprehend perpetrators.

Facial recognition using keypoint annotation
Video annotation for computer vision and robotics

Video annotation for computer vision and robotics

Industrial robots are being taught to see with iMerit video annotation. These perceptive robots are adaptive to their environment, allowing them to respond to their environment without any human interaction. This automation is creating high production and less human accidents.

Create larger harvest yields with computer vision

Farmers use computer vision to monitor their crops for pests and plant diseases. Through the use of footage collected by drones, iMerit experts can teach a model to recognize pests and potential threats to crop fields by annotating the footage.

Create larger harvest yields with computer vision
Optimal athletic performance with computer vision

Optimal athletic performance with computer vision

Virtual training and home workouts can use computer vision to coach clients on form, posture, and performance. iMerit experts use video annotation to teach sports AI models how to recognize when a client is performing in a way that puts them at risk for injury or challenges their performance.




Video data points annotated




Getting started!

The need for speed in high-quality video annotation has never been greater. iMerit combines the best predictive and automated annotation technology with world-class data annotation experts and subject matter experts to deliver the data you need to get to production, fast.

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