OBJECT DETECTION BY STEREO VISION IMAGES Since both theoretical and practical aspects of the developments in this field of research are explored, including recent state-of-the-art technologies and research opportunities in the area of object detection, this book will act as a good reference for practitioners, students, and researchers. Current state-of-the-art technologies have opened up new opportunities in research in the areas of object detection and recognition of digital images and videos, robotics, neural networks, machine learning, stereo vision matching algorithms, soft computing, customer prediction, social media analysis, recommendation systems, and stereo vision. This book has been designed to provide directions for those interested in researching and developing intelligent applications to detect an object and estimate depth. In addition to focusing on the performance of the system using high-performance computing techniques, a technical overview of certain tools, languages, libraries, frameworks, and APIs for developing applications is also given. More specifically, detection using stereo vision images/video from its developmental stage up till today, its possible applications, and general research problems relating to it are covered. Also presented are techniques and algorithms that satisfy the peculiar needs of stereo vision images along with emerging research opportunities through analysis of modern techniques being applied to intelligent systems. Audience Researchers in information technology looking at robotics, deep learning, machine learning, big data analytics, neural networks, pattern & data mining, and image and object recognition. Industrial sectors include automotive electronics, security and surveillance systems, and online retailers.

Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications. Places an emphasis on tensor and statistical based approaches within object detection and recognition. Provides an overview of image clustering and classification methods which includes subspace and kernel based processing, mean shift and Kalman filter, neural networks, and k-means methods. Contains numerous case study examples of mainly automotive applications. Includes a companion website hosting full C++ implementation, of topics presented in the book as a software library, and an accompanying manual to the software platform.

Over the last decade, significant progress has been made in 3D imaging research. As a result, 3D imaging methods and techniques are being employed for various applications, including 3D television, intelligent robotics, medical imaging, and stereovision. Depth Map and 3D Imaging Applications: Algorithms and Technologies present various 3D algorithms developed in the recent years and to investigate the application of 3D methods in various domains. Containing five sections, this book offers perspectives on 3D imaging algorithms, 3D shape recovery, stereoscopic vision and autostereoscopic vision, 3D vision for robotic applications, and 3D imaging applications. This book is an important resource for professionals, scientists, researchers, academics, and software engineers in image/video processing and computer vision.

This book presents research trends on computer vision, especially on application of robotics, and on advanced approachs for computer vision (such as omnidirectional vision). Among them, research on RFID technology integrating stereo vision to localize an indoor mobile robot is included in this book. Besides, this book includes many research on omnidirectional vision, and the combination of omnidirectional vision with robotics. This book features representative work on the computer vision, and it puts more focus on robotics vision and omnidirectioal vision. The intended audience is anyone who wishes to become familiar with the latest research work on computer vision, especially its applications on robots. The contents of this book allow the reader to know more technical aspects and applications of computer vision. Researchers and instructors will benefit from this book.

Image-based rendering, as an area of overlap between computer graphics and computer vision, uses computer vision techniques to aid in sythesizing new views of scenes. Image-based rendering methods are having a substantial impact on the field of computer graphics, and also play an important role in the related field of multimedia systems, for applications such as teleconferencing, remote instruction and surgery, virtual reality and entertainment. The book develops a novel way of formalizing the view synthesis problem under the full perspective model, yielding a clean, linear warping equation. It shows new techniques for dealing with visibility issues such as partial occlusion and "holes". Furthermore, the author thoroughly re-evaluates the requirements that view synthesis places on stereo algorithms and introduces two novel stereo algorithms specifically tailored to the application of view synthesis.

This two-volume set (CCIS 201 and CCIS 202) constitutes the refereed proceedings of the International Conference on Computer Science and Education, CSE 2011, held in Qingdao, China, in July 2011. The 164 revised full papers presented in both volumes were carefully reviewed and selected from a large number of submissions. The papers address a large number of research topics and applications: from artificial intelligence to computers and information technology; from education systems to methods research and other related issues; such as: database technology, computer architecture, software engineering, computer graphics, control technology, systems engineering, network, communication, and other advanced technology, computer education, and life-long education.

Dr.Dhanalakshmi, Indian Institute of Information Technology Design and Manufacturing Kancheepuram (IIITD&M K), Chennai, Tamil Nadu, India. Dr.P.Murugabharathi, Guest Faculty, Mother Teresa Women's University Research and Extension Centre, Chennai, Tamil Nadu, India. Mrs.R.A.Latha Devi, Assistant Professor, Department of Mathematics, Sri Meenakshi Govt. Arts College for Women, Madurai, Tamil Nadu, India. Mrs.V.Suganthi, Assistant Professor, Department of Computer Science, C.T.T.E College for Women, Chennai,Tamil Nadu, India. Mr.K.Madhavan, Ph.D Research Scholar, Department of Computer Science, University of Madras, Guindy Campus,Chennai, Tamil Nadu, India.

This book proposes new technologies and discusses future solutions for ICT design infrastructures, as reflected in high-quality papers presented at the 5th International Conference on ICT for Sustainable Development (ICT4SD 2020), held in Goa, India, on 23–24 July 2020. The conference provided a valuable forum for cutting-edge research discussions among pioneering researchers, scientists, industrial engineers, and students from all around the world. Bringing together experts from different countries, the book explores a range of central issues from an international perspective.

This book presents a remarkable collection of chapters covering a wide range of topics in the areas of Computer Vision, both from theoretical and application perspectives. It gathers the proceedings of the Computer Vision Conference (CVC 2019), held in Las Vegas, USA from May 2 to 3, 2019. The conference attracted a total of 371 submissions from pioneering researchers, scientists, industrial engineers, and students all around the world. These submissions underwent a double-blind peer review process, after which 118 (including 7 poster papers) were selected for inclusion in these proceedings. The book’s goal is to reflect the intellectual breadth and depth of current research on computer vision, from classical to intelligent scope. Accordingly, its respective chapters address state-of-the-art intelligent methods and techniques for solving real-world problems, while also outlining future research directions. Topic areas covered include Machine Vision and Learning, Data Science, Image Processing, Deep Learning, and Computer Vision Applications.

Mobile robots are the focus of a great deal of current research in robotics. Mobile robotics is a young, multidisciplinary field involving knowledge from many areas, including electrical, electronic and mechanical engineering, computer, cognitive and social sciences. Being engaged in the design of automated systems, it lies at the intersection of artificial intelligence, computational vision, and robotics. Thanks to the numerous researchers sharing their goals, visions and results within the community, mobile robotics is becoming a very rich and stimulating area. The book Recent Advances in Mobile Robotics addresses the topic by integrating contributions from many researchers around the globe. It emphasizes the computational methods of programming mobile robots, rather than the methods of constructing the hardware. Its content reflects different complementary aspects of theory and practice, which have recently taken place. We believe that it will serve as a valuable handbook to those who work in research and development of mobile robots.