Best Books on Visual Semantics

“Semantic-based Visual Information Retrieval” Book Review: This book is for researchers, students, and practitioners who want to learn about accessing and searching visual media databases effectively. It offers the latest advancements in the field and provides useful tools for interacting with and retrieving information from these databases. The book focuses on semantic-based visual information retrieval and covers important topics like representing and describing visual content at different levels, understanding scenes, creating semantic models, annotating images and videos, and improving human-computer interaction. It also offers practical solutions for various real-world applications.

“Visual Knowledge Modeling for Semantic Web Technologies” Book Review: This book is designed to help individuals understand and use visual knowledge modeling. It introduces a visual language that is easy to understand and use. The book explains how to use this visual language to organize thoughts, analyze information, and turn it into personal knowledge. It also shows how visual knowledge modeling can support collaborative activities and help people acquire knowledge. The goal of the book is to make this intellectual method and set of tools accessible to everyone.

“Visual Analysis of Behaviour” Book Review: This book provides a detailed study of analyzing behavior using computational models and algorithms. It covers topics such as learning group activities, profiling behavior without supervision, discovering hierarchical behaviors, and understanding behavioral context. It also explores rare behaviors, active learning with human input, correlating behaviors from multiple cameras, and identifying individuals. The book discusses abnormal behavior detection, using techniques like Bayesian information criterion and Bayesian networks. It delves into hidden conditional random fields, hidden Markov models, and analyzing human silhouette shapes. Other topics covered include latent Dirichlet allocation, local binary patterns, spectral clustering, and support vector machines.

“Towards Semantic and Effective Visual Codebooks” Book Review: This book focuses on the study of visual vocabularies for category-level object recognition. Its objective is to not only obtain more discriminative and compact visual codebooks but also bridge the gap between visual features and semantic concepts. The book presents a novel approach for acquiring class representative visual words. It introduces a clustering aggregation-based approach for constructing effective visual vocabularies. Additionally, it describes a framework for incorporating meaningful spatial coherence among local features into the construction of the visual codebook. The book also provides an efficient high-dimensional data clustering algorithm and the Fast Reciprocal Nearest Neighbors method. Furthermore, it includes a new database of images called the Image Collection of Annotated Real-world Objects (ICARO), specifically designed for evaluating category-level object recognition systems.