View-based 3-D Object Retrieval

Content-based 3-D object retrieval has attracted extensive attention recently and has applications in a variety of fields, such as, computer-aided design, tele-medicine,mobile multimedia, virtual reality, and entertainment. The development of efficient and effective content-based 3-D object retrieval techniques has enabled the use of fast 3-D reconstruction and model design. Recent technical progress, such as the development of camera technologies, has made it possible to capture the views of 3-D objects. As a result, view-based 3-D object retrieval has become an essential but challenging research topic. View-based 3-D Object Retrieval introduces and discusses the fundamental challenges in view-based 3-D object retrieval, proposes a collection of selected state-of-the-art methods for accomplishing this task developed by the authors, and summarizes recent achievements in view-based 3-D object retrieval. Part I presents an Introduction to View-based 3-D Object Retrieval, Part II discusses View Extraction, Selection, and Representation, Part III provides a deep dive into View-Based 3-D Object Comparison, and Part IV looks at future research and developments including Big Data application and geographical location-based applications. - Systematically introduces view-based 3-D object retrieval, including problem definitions and settings, methodologies, and benchmark testing beds - Discusses several key challenges in view-based 3-D object retrieval, and introduces the state-of-the-art solutions - Presents the progression from general image retrieval techniques to view-based 3-D object retrieval - Introduces future research efforts in the areas of Big Data, feature extraction, and geographical location-based applications

Yue Gao is with the Department of Automation, Tsinghua University. His recent research focuses on the areas of neuroimaging, multimedia and remote sensing. He is a senior member of IEEE.