Besides identifying objects, video annotation is implied to build the training data set for AI models. It helps to localize the items in the video for object localization. A video comprises several objects and by localizing them, you can discover the primary object in the image. The key objective of object localization is to anticipate the item in an image and its limits.
The other objective of video annotation involves training the computer, machine learning and AI models to understand the movements of humans and predicting postures. This is mostly seen in sports areas to monitor the activities of athletes during sports events and contests. It allows automated machines and robots to understand human postures.
Video annotation also captures the object of interest and makes it readable by machines frame by frame. The moving objects display on the screen and are labelled using a particular tool for precise recognition through machine learning tactics to train AI models built on visual perception.