Learning spiral provides video annotation services to provide accurate data for self-driving cars and many other use cases. Build comprehensively labeled video datasets with Learning Spiral suite of video annotation services. From object localization to video tracking, Learning Spiral has the experience and technology necessary to serve all of your video annotation needs. The first and most use and purpose of video annotation is capturing the object of interest frame-by-frame and making it recognizable to machines.
Use Of VIDEO ANNOTATION
The first and most use and purpose of video annotation is capturing the object of interest frame-by-frame & making it recognizable to machines. Video annotation will provide an in-depth visual perception to autonomous vehicles recognizing the various types of objects like pedestrians, street lights, signboards, traffic lanes, signals, cyclists and vehicles moving on the road.
Any AI system that processes visual information usually relies on computer vision, and those capable of identifying specific objects. Object Detection is the process of finding real-world object instances like car, bikes, TV, flowers, and humans in still images or Videos. It allows for the recognition and detection of multiple objects within an image Object detection provides us with a much better understanding of an image as a whole. It is commonly used in applications such as image retrieval, security, surveillance, and advanced driver assistance systems( ADAS).
Video & Motion Tracking
The first and foremost use of Video & Motion Tracking is capturing the object of interest frame-by-frame and making it recognizable to machines. It will provide an in-depth visual perception to autonomous vehicles recognizing the various types of objects. It’s basically done to Train machines on roads. Learning spiral provides video annotation services to provide accurate data for self-driving cars and many more use cases.
Track Human Activity and Pose Estimation
Why is Video Annotation necessary?
It’s a very important task for machine learning because data scientists need to use clean, annotated data to train machine learning models. Data annotation is important in machine learning in many use cases.
Data Annotation makes the work of the machine learning program much easier and accurate.
Video Annotation = Improves the accuracy of data
Video Annotation = Better quality training data
Video Annotation = Better results
It’s one of the most initial and important steps
VIDEO ANNOTATION TOOLS
- UltimateLabeling – A multi-purpose Video Labeling GUI in Python with integrated SOTA detector and tracker
- VATIC – VATIC is an online video annotation tool for computer vision research that crowdsources work to Amazon’s Mechanical Turk.
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