Computer Vision

This comprehensive text/ book presents a broad review of both traditional (i.e., conventional) and the deep learning aspects of object detection in various adversarial conditions of real-world in a clear, insightful, and highly comprehensive style. Beginning with the relation of computer vision and object detection, the text covers the various representation of objects, applications of object detection, and challenges of real-world faced by the research community for object detection task. The book addresses various degradations and artifacts of real-world for object detection task and also highlights the impacts of artifacts in the object detection problems. The book covers various imaging modalities and benchmark datasets mostly adopted by the research community for solving various aspects of object detection tasks. The book also collects together solutions and perspectives proposed by the pre-eminent researchers in the field, addressing not only the background of visibility enhancement, but also techniques proposed in the literature for visibility enhancement of scenes and detection of objects in various representative challenges of real-world.Computer Vision: Object Detection in Adversarial Vision is unique for its diverse content, clear presentation, and overall completeness. It provides a clear, practical, and detailed introduction and advancement of object detection in various representative challenging conditions of real world.Topics and Features:· Offers the first truly comprehensive presentation of aspects of the object detection in degraded and non-degraded environment.· Include in depth various degradation and artifacts, and impact of those artifacts in real-world for solving the object detection problems.· Give detailed visual examples of applications of object detection in real-world.· Presents a detailed description of popular imaging modalities adopted by the researchers for object detection.· Presents the key characteristics of various benchmark datasets in indoor and outdoor environment for solving object detection tasks.· Surveys the complete field of visibility enhancement of degraded scenes, including conventional methods designed for enhancing the degraded scenes as well as the deep architectures.· Discusses techniques for detection of objects in real-world applications.· Contains various hands-on practical examples and tutorial for solving object detection problems using python.· Motivates readers to build vision based systems for solving the object detection problems in degraded and non-degraded challenges of real-world.The book will be of great interest to a broad audience ranging from researchers and practitioners, graduate and post graduate students involved in computer vision task with respect to object detection in degraded and non-degraded vision problems of real-world.

Mrinal Kanti Bhowmik received the Bachelor of Engineering (B.E.) degree in Computer Science and Engineering from the Tripura Engineering College in 2004, the Master of Technology (M. Tech) degree in Computer Science and Engineering from Tripura University (A Central University), India, in 2007, and the Ph.D. degree in Engineering from Jadavpur University, Kolkata, India, in 2014. He has also spent Fall 2022 as a DST-SERB International Research Experience (SIRE) Scholar with SIRE Fellowship, sponsored by Science and Engineering Research Board (SERB), Government of India at the NYU Center for Cybersecurity (CCS), Tandon School of Engineering, New York University, New York City. He has successfully completed two Department of Electronics and Information Technology (DeitY) (Now Ministry of Electronics and Information Technology (MeitY)) funded projects, one Department of Biotechnology (DBT)-Twinning project, one Society for Applied Microwave Electronics Engineering and Research (SAMEER) funded project, one Indian Council of Medical Research (ICMR) project, and one Defence Research and Development Organisation (DRDO) project as the Principal Investigator. He is currently the Principal Investigator of one Department of Biotechnology (DBT) funded project and Co-Principal Investigator of one Indian Council of Medical Research (ICMR) project in collaboration with All India Institute of Medical Sciences (AIIMS), New Delhi. Since July 2010, he has been serving with the Department of Computer Science and Engineering, Tripura University as an Assistant Professor. He was awarded the Short Term Indian Council of Medical Research (ICMR), Department of Health Research (DHR) International Fellowship from 2019 to 2020 as a Senior Indian Biomedical Scientist for bilateral cooperation in cross-disciplinary research area (i.e., biomedical diagnostic and inferencing systems). His research team has also designed two datasets for object detection in degraded vision named as Extended Tripura University Video Dataset (E-TUVD) and Tripura University Video Dataset at Night time (TU-VDN) dataset for the research community in the proposed domain of object detection. His current research interests are in the field of computer vision, security and surveillance, medical imaging, and image and video forensics.