Train your machine learning algorithms through labeled videos with added metadata to make the objects recognizable in picture-videos. Here at Cogito, we expertise in labeling such videos using various techniques of image annotation to capture each object in the video frame-by-frame.
Video annotation will provide an in-depth visual perception of autonomous vehicles by recognizing various types of objects like the pedestrians, street lights, signboards, traffic lanes, signals, cyclists, or vehicles moving on the road. Cogito provides a frame annotation service using a video annotation tool, to build a ground truth AI model for self-driving.
In video annotation, images are annotated using various image annotation techniques. It can label certain parts of the image to full segmentation. Every pixel is annotated with its semantic meaning, helping the Computer Vision model to work with its highest quality. Cogito works with video segmentation annotation for a visual-based perception model.
Video annotation service also helps to recognize human activities and their postures. A precisely annotated moving image helps machines to recognize facial expressions of humans and how they pose while performing various actions. Cogito provides the best quality annotated videos with a state-of-the-art facility to track all human actions.
We are equipped with a full range of video annotation services which are used to improve the AI and machine learning algorithm training accuracy for appropriate prediction. Our highly-skilled team of annotators is capable of annotating different categories of videos with high levels of accuracy. This ensures that the objects are recognizable even at a fast moving speed in a video recording.
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