There is no denying that every application of computer vision depends on annotated images for training, testing and authenticating the models that rule them. When it comes to these image annotations, it varies in complexity as it ranges from simple to complex pixel-by-pixel classification. The tools supporting such tasks differ in complexity and quality too. Regardless of the differences in the process, annotating images is regarded to be a cumbersome and costly process.
Although numerous solutions are there to reduce the resources it requires in annotating a single image, such as pre annotation and assisted annotation techniques, the ideal solution that helps to overcome the unavoidable hurdles of annotating images is video annotation. When you collect and annotate videos instead of images, it not only pays large dividends in terms of speed and size of the training dataset outcome, but also there is more competence and effectiveness in the process.
When the developers use the right tool, not only does it make the process more effective and successful but saves their time too. Annotating a video is more advantageous than annotating an image.