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The era of big data has ushered in an exponential growth of multimedia content, including videos, which are becoming increasingly prevalent in various domains, such as entertainment, surveillance, healthcare, and autonomous systems. Videos contain a wealth of information, but to unlock their full potential, it is crucial to accurately label and annotate the data they contain. Video data labeling plays a pivotal role in enabling machine learning algorithms to understand and analyze videos, leading to a wide range of applications such as video classification, object detection, action recognition, and video summarization.
In this chapter, we will explore the fascinating world of video data classification. Video classification involves the task of assigning labels or categories to videos based on their content, enabling us to organize, search, and analyze video data efficiently. We will explore different use cases where video classification plays a crucial role and learn how to label video data, using Python and a public dataset.