Методи семантичного аналізу відеоданих

Abstract

Semantic analysis of video data involves extracting meaningful information and understanding the context and objects within the video content. With the rapid growth of video data in recent years, there has been a significant interest in developing techniques for automatic interpretation. This report explores various methods for semantic analysis, including object recognition, activity recognition, scene understanding, and deep learning-based approaches. The use of convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for analyzing temporal and spatial data is discussed, alongside challenges such as data complexity, scalability, and real-time processing.