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.
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.
Similar to 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.
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.
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.
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.
Polygon Annotation
It involves 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.
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.
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.
Semantic Segmentation
It 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.
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.
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 needs high-quality training datasets. Depending the 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.
95% high accuracy
Our video annotation services will provide you with guaranteed high quality video annotation with specific stress on high accuracy.
cost-effective pricing
Our pricing plan is tailored to fit within your video annotation project budget by providing room for negotiations and agreements.
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.
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.
1000+
Trained Experts
95%+
Accuracy
50+
Happy Clients
450+
Successful Projects
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
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 : 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 : 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 : 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 : 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.
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 : 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 : 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 : 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 : 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.
Video Annotation Use Cases Across Various Industries
Autonomous vehicles
healthcare
retail & e-commerce
Retail stores use annotated video data to train machine learning algorithms to identify stock levels on an ongoing basis. 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.
manufacturing
Geospatial technology
Video clips are 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.
government
sports & games
security & Surveillance
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.