Video
In this section, we are going to discuss how to use CNNs with videos and the different techniques that we can use.
Classifying videos with pretrained nets in six different ways
Classifying videos is an area of active research because of the large amount of data needed for processing this type of media. Memory requirements are frequently reaching the limits of modern GPUs and a distributed form of training on multiple machines might be required. Researchers are currently exploring different directions of investigation, with increasing levels of complexity from the first approach to the sixth, as described below. Let’s review them:
- The first approach consists of classifying one video frame at a time by considering each one of them as a separate image processed with a 2D CNN. This approach simply reduces the video classification problem to an image classification problem. Each video frame “emits” a classification output, and the video is...
