Video Annotation Services

Video annotation services help create high quality video annotation datasets for training machine learning algorithms to recognize objects in the real world and carry out specific actions.

The image shows how video annotation is done

Video Annotation Services

Video annotation services help create high quality video annotation datasets for training machine learning algorithms to recognize objects in the real world and carry out specific actions.

What Is Video Annotation?

Video annotation is the process by which tags, labels, marks, or annotations are added to moving objects in video clips. Also known as video labeling, the video annotation process involves adding annotation to help identify objects in different video frames.

Like image annotation, the video is divided into component segments called video frames and objects of interest annotated on a frame-by-frame basis. Video annotation provides video datasets that offer high-quality training data for training AI models.

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Different Types Of Video Annotation Techniques

The choice of video annotation technique depends on the intended objective of the annotated data. Different video annotation projects require different annotation techniques. It is, therefore, essential to ensure that the right annotation technique is used based on the video annotation requirements. Some of the commonly used video annotation techniques to choose from are discussed below.

The image shows an empty road with dashed lines referring to polyline annotation

Polyline Annotation

Polyline annotation  is also called lines or spline annotation. It involves drawing continuous lines on objects of interest. The technique is mostly used to create datasets for training lidar applications to avoid crossing their lane onto other vehicles.

 

The image shows a road full of vehicles referring to 2D bounding boxes

2D Bounding Boxes

2D bounding box annotation involves drawing a box around the edges of the annotation object. Bounding boxes are the most commonly used data annotation technique for creating video datasets for training computer vision models to identify objects in real life.

The image shows a few cars lined up on a road and referring to polygon annotation

Polygon Annotation

Polygon Annotations involve placing dots along the edges of the annotation object and then joining the dots to create an outline of the shape of the object of interest. It is used to capture the actual form of irregularly shaped objects where bounding boxes cannot achieve the same.

 The image shows a lady and many labels on her face referring to the landmark annotation

Landmark Annotation

Landmark annotation involves plotting key points on the shape of the annotation object. Its versatility makes it useful to annotate video objects of any shape variations. The plotted key points are then used to train computer vision models to identify and classify objects of similar appearance in real life.

 

The image shows a road with lots of cars and refers to the 3D cuboid annotation service

3D Cuboid Annotation

3D cuboid annotation involves creating a 3D world depiction from 2D objects using cuboids for computer vision algorithms. The cuboids, in addition to length and width, also provide computer vision models with information about the depth of the objects, allowing them to recognize objects better in the real world.

 

The image shows a woman labeled in green, blue labeled cars, and yellow  labeled road referring to semantic segmentation

Semantic Segmentation

Semantic Segmentation is a data annotation technique where an object of interest is annotated at the pixel level. In the video annotation process, an annotation object is annotated at the pixel level in each video frame and assigned a single predefined class throughout the entire video.

The image shows a man is playing golf and refers to keypoint annotation

Keypoint annotation

Keypoint annotation is quite similar to landmark annotation. It involves placing key points on specific points of interest in an annotation object. The key point can then be used to train algorithms to identify one object relative to another, such as in sports.

 

The image shows many cars on road labeled by green boxes and referring to event tracking and classification

Event Tracking & Classification

It involves obtaining raw video data and using it to train computer vision to identify, classify, and track object actions through multiple video frames. The AI model is trained to identify specific movements in an object and follow the same through multiple stages in a video clip.

Video annotation services for Driverless Cars, Computer Vision Models, ADAS, and Object Tracking

Training computer vision models to carry out different actions need high-quality training datasets. Depending on the project object, different annotation types can be used to produce high-quality video annotation. Our video annotator experts have experience working with varying annotation techniques and will annotate videos to suit your AI training data needs.

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95% high accuracy

Our video annotation services will provide you with guaranteed high quality video annotation with specific stress on high accuracy.

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cost-effective pricing

Our pricing plan is tailored to fit within your video annotation project budget by providing room for negotiations and agreements.

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data security

At Annotation Box, we are fully committed to data security and have invested heavily to ensure the data you give remains with us.

The image shows various image annotation techniques to achieve precision in annotation

Why Choose Us?

At Annotation Box, our data annotation services are tailored to fit specific client video annotation project needs. Our experienced video annotation experts will work with you throughout your annotation project to create high quality video annotations.

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1000+

Trained Experts

9+ Accuracy-01

95%+

Accuracy

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50+

Happy Clients

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450+

Successful Projects

The doodle shows a laptop with many video files referring raw file for video annotation

Get Us Onboard For Video Annotation Services

Outsourcing video annotation can make or break your project, and at Annotation Box, we are committed to working together to achieve your project’s success.

How We Work

Get your data annotated in just 5 simple steps.

step

STEP : 1

 Project Assessment

Upon receiving the inquiry we assign experts to understand your project requirements. After in-depth research by our experts and assessing your requirements, we deploy the best data annotation solution for you.

step

STEP : 2

Sample Data Labeling

After deploying data annotation solution. We begin our work. The first step is to ask for your samples. Once we receive your samples, we run sample data labeling. We label the samples and send you back for your review.

step

STEP : 3

Training

Once you’re satisfied with our sample. We deploy a training module for the team to impart an in-depth understanding of the project.
Our Quality analyst keeps checking for the desired quality output with our annotators.

step

STEP : 4

Production

Our dedicated project manager will oversee the team and monitor them constantly to ensure the annotators are meeting the desired output quality set initially and completing the project on time. Annotation Box puts accuracy first and foremost.

step

STEP : 5

Evaluation

We believe in transparency and high-quality data annotation. Through our continuous feedback cycle, we make sure the annotation is done correctly. Our flexible workforce enables us to scale up production at any time.

RIVEW

STEP : 1

 Project Assessment

Upon receiving the inquiry we assign experts to understand your project requirements.

After in-depth research by our experts and assessing your requirements, we deploy the best data annotation solution for you.

step

STEP : 2

Sample Data Labeling

One of the finest translation agencies I have come across lately. The friendly experts know what is required and deliver better than expected.They were receiving all my calls during the process. The best part is they are affordable.

step

STEP : 3

Training

Once you’re satisfied with our sample. We deploy a training module for the team to impart an in-depth understanding of the project.Our Quality analyst keeps checking for the desired quality output with our annotators.

step

STEP : 4

Production

Our dedicated project manager will oversee the team and monitor them constantly to ensure the annotators are meeting the desired output quality set initially and completing the project on time. Annotation Box puts accuracy first and foremost.

step

STEP : 5

Evaluation

We believe in transparency and high-quality data annotation. Through our continuous feedback cycle, we make sure the annotation is done correctly. Our flexible workforce enables us to scale up production at any time.

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Video Annotation Use Cases Across Various Industries

Video annotation is a valuable tool for advancing AI in many industries. It provides more helpful information than image annotation, including more data on the object’s context. While it is more time-consuming, video annotation has found application in several industries, as discussed below.

The doodle shows autonomous vehicle working properly because of proper Data collection by AnnotationBox

Autonomous vehicles

Video annotation for autonomous vehicles that seemed a distant dream is becoming a reality. Video annotation is used to create training datasets for training computer vision-based models to recognize objects in the real world. It is mainly used in Lidar to help self-driving vehicles learn to identify lanes on roads and other objects of interest, such as powerlines and sidewalks.

 The doodle shows data collection services by AnnotationBox enhancing healthcare

healthcare

Video annotation for healthcare, the video annotation process is used to help physicians and medical practitioners train medical AI to identify specific cells in the body as observed under the microscope. It is also used to help machine learning algorithms understand medical videos and help in medical diagnosis.

 The doodle shows a retail store referring to data collection services by AnnotationBox enhancing retail sector

retail & e-commerce

Video annotation for retail and eCommerce stores uses annotated video data to train machine learning algorithms to identify stock levels continuously. Combined with deep learning, AI models are trained to understand and predict human movements in stores and e-commerce platforms, informing where to place the most selling products.

 The image shows flowchart of manufacturing services and how AI helps

manufacturing

Video annotation for manufacturing,This machine learning models are trained using annotated video footage to understand and perform highly repetitive tasks in the manufacturing process. Each frame in the video footage is annotated to capture certain events of interest. The resulting datasets are then used to train AI models to understand the required objects or perform the requisite tasks.

The image shows geospatial technology is used to do video annotation

Geospatial technology

Video animation for geospatial technology clips is annotated to train machine learning models to interpret satellite and drone footage. The AI algorithms are trained to identify features, patterns, and terrains on the ground that are useful in identifying and planning natural resources. For instance, through AI, scientists can recognize land use changes contributing to the drying of wetlands in different areas worldwide.

 

The doodle shows the government taking data collection services by AnnotationBox to maximize its accuracy in different sectors

government

Across the world, video annotation for governments is implementing artificial intelligence to help secure borders, monitor maritime activities, and maintain security through early threat detection in crowded places. Annotated video data is used to train AI models to understand human emotions and expressions that, combined with computer vision, are then used to analyze human intent, which is helpful in threat detection by law enforcement.

The doodle shows few players of different sports and how video annotation works for games and sports

sports & games

Video annotation for sports and games plays a critical role through virtual assisted referees. High-quality datasets are used to train machine learning models to understand the actions of one object relative to other objects. For instance, AI models in football are trained to understand the ball’s position relative to the player’s body and decide whether a foul has occurred.

The doodle shows how security and surveillance is enhanced with the help of AnnotationBox

security & Surveillance

Video annotation for security uses video datasets to identify and distinguish between different individuals in a crowd. It’s used in security and surveillance, where security companies use facial recognition to identify people involved in crimes. Furthermore, AI algorithms are trained using annotated videos to identify individuals carrying out specific acts, such as shoplifting or exhibiting certain facial expressions, which is useful in the surveillance of retail stores.

Video Annotation Services – FAQs

Here are answers to some of the common questions you might have about video annotation services.

when IS video Annotation USED?

The annotation type for your project entirely depends on the objectives you seek to accomplish. For some projects, image annotation is acceptable, but for some, annotating videos is the way to go. For instance, if your project seeks to train a machine learning algorithm to understand video output from surveillance cameras, then video annotation is the best annotation type.

Video annotation should also be used when the context of an action or object is vital to helping AI make the right decision. For instance, a person may shoplift an item and later return it. Image annotation makes it impossible to know the item was returned, but video annotation gives that context.

Will video annotation services cost more?

Annotating video is time-consuming and generally costs more as one video clip has multiple frames. Depending on the number of objects of interest in each frame, video annotation is more cost-effective than image annotation, as a client can get more objects annotated.

Will my image annotation services provider work on MY VIDEO ANNOTATION project?

Some annotation service providers have specialized in specific annotation types. Before trusting your video annotation project with the same company that worked on your image annotation project, first confirm that they can deliver high-quality video annotations. That should include looking if they have any experience in this area. To avoid inconsistencies with your projects, you can also look for an all-around video annotation service provider such as Annotation Box.

How many videos Should I USE IN MY PROJECT?

Creating high quality training datasets requires huge volumes of video data. The number is primarily driven by the scale and scope of the project and the machine learning models to be trained. Therefore, it is impossible to give specific numbers until the project objectives and scare are properly defined. However, training datasets should be enough for the training and testing of the model.

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