Intelligent Image and Video Analytics: Clustering and Classification Applications

Video data mining and analytics extract low and high-level features to build predictive computational models using machine-learning algorithms. This book covers essential topics, emerging methods, and potential applications in intelligent systems, data mining, knowledge discovery, big data analytics, machine learning, neural network, and deep learning. It focuses on multimodality video analytics and recent advances in research and applications.

Format: Hardback
Length: 338 pages
Publication date: 12 April 2023
Publisher: Taylor & Francis Ltd

Video is a rich source of information that encompasses various types of data, including meta-data, visual, audio, spatial, and temporal data. This wealth of information can be analyzed to extract a wide range of low-level and high-level features, which can then be used to build predictive computational models using machine-learning algorithms. By leveraging these algorithms, researchers can discover interesting patterns, concepts, relationships, and associations within the video data.

This book serves as a comprehensive review of essential topics in video data mining and analytics. It delves into emerging methods and potential applications of video data mining and analytics, integrating areas such as intelligent systems, data mining, knowledge discovery, big data analytics, machine learning, neural networks, and deep learning. The focus is particularly on multimodality video analytics, which involves the analysis of multiple modalities (e.g., visual, audio, and spatial data) in a single video.

The book provides up-to-date coverage of the state-of-the-art techniques in intelligent video analytics. It explores important applications that require techniques from both artificial intelligence and computer vision, such as video surveillance, action recognition, and medical imaging. Multimodality video analytics is also discussed, with a focus on its applications in various domains, including smart environments, smart homes, and smart cities.

One of the key aspects of this book is its examination of issues related to multimodality data fusion. Multimodality data refers to the combination of data from different modalities, and it is becoming increasingly important in many applications. The book highlights research challenges related to multimodality data fusion and discusses potential solutions and techniques.

To facilitate the integration of various techniques from video processing, data mining, and machine learning, the book adopts a multidisciplinary approach. It provides a comprehensive overview of the relevant theories, algorithms, and methodologies, making it accessible to researchers, professionals, and graduate students in image processing, video analytics, computer science and engineering, signal processing, machine learning, and electrical engineering.

In conclusion, this book is a valuable resource for anyone interested in video data mining and analytics. It offers a comprehensive coverage of the state-of-the-art techniques, important applications, and research challenges in the field. By integrating various disciplines, the book provides a multidisciplinary perspective on video data mining and analytics, making it an essential tool for researchers, professionals, and graduate students alike.

Dimension: 234 x 156 (mm)
ISBN-13: 9780367512989