With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contrast to single object tracking, multi-target introduces one extra step of detection. Tracking multi-target includes detecting and categorizing the target into multiple classes in the first frame and provides each individual target an ID to keep its track in the subsequent frames of a video stream. One category of multi-target algorithms exploits global information to track the target of the detected target. On the other hand, some algorithms consider present and past information of the target to provide efficient tracking solutions. Apart from these, deep leaning-based algorithms provide reliable and accurate solutions. But, these algorithms are computationally slow when applied in real-time. This book presents and summarizes the various visual tracking algorithms and challenges in the domain. The various feature that can be extracted from the target and target saliency prediction is also covered. It explores a comprehensive analysis of the evolution from traditional methods to deep learning methods, from single object tracking to multi-target tracking. In addition, the application of visual tracking and the future of visual tracking can also be introduced to provide the future aspects in the domain to the reader. This book also discusses the advancement in the area with critical performance analysis of each proposed algorithm. This book will be formulated with intent to uncover the challenges and possibilities of efficient and effective tracking of single or multi-object, addressing the various environmental and hardware challenges.
The intended audience includes academicians, engineers, postgraduate students, developers, professionals, military personals, scientists, data analysts, practitioners, and people who are interested in exploring more about tracking.· Another projected audience are the researchers and academicians who identify and develop methodologies, frameworks, tools, and applications through reference citations, literature reviews, quantitative/qualitative results, and discussions.
Tabla de materias
Single Object Detection from Video Streaming.- Different Approaches to Background Subtraction and Object Tracking in Video Streams: A Review.- Auto Alignment of Tanker Loading Arm Utilizing Stereo-Vision Video and 3D Euclidean Scene Reconstruction.- Visual Object Segmentation Improvement using Deep Convolutional Neural Networks.- Applications of Deep Learning based Methods on Surveillance Video Stream by Tracking Various Suspicious Activities.- Hardware Design Aspects of Visual Tracking System.- Automatic Helmet (Object) Detection and Tracking the Riders using Kalman Filter Technique.- Deep Learning based Multi-Object Tracking.- Multiple Object Tracking of Autonomous Vehicles for Sustainable and Smart Cities.- Multi Object Detection: A Social Distancing Monitoring System.- Investigating Two Stage Detection Methods Using Traffic Light Detection Dataset.
Sobre el autor
Dr. Ashish Kumar, Ph.D., is working as an assistant professor with Bennett University, Greater Noida, U.P., India. He has completed his Ph.D. in computer science and engineering from Delhi Technological University (formerly DCE), New Delhi, India in 2020. He has received best researcher award from the Delhi Technological University for his contribution in the computer vision domain. He has completed M.Tech in computer Science and engineering from GGS Indraprastha University, New Delhi. He has published many research papers in various reputed national and international journals and conferences. His current research interests include object tracking, image processing, artificial intelligence, and medical imaging analysis.
Dr. Rachna Jain, currently working as Associate Professor (IT Department) in Bhagwan Parshuram Institute of Technology (GGSIPU) since Aug 2021. She did her PHD from Banasthali Vidyapith (Computer Science) in 2017.She received ME degree in year 2011 from Delhi college of engineering (Delhi University) with specialization in Computer Technology and Applications. Her current research interests are Cloud Computing, Fuzzy Logic, Network and information security, Swarm Intelligence, Big Data and Io T, Deep Learning and Machine Learning. She has contributed with more than 20 book chapters in various books. She has also served as Session Chair in various International Conferences. She completed DST Project titled “Design an autonomous intelligent drone for city surveillance” as CO-PI. A total of 16+ Years of Academic / Research Experience with more than 100+ Publications in various National, International Conferences cum International Journals (Scopus/ISI/SCI) of High Repute.
Dr. V. Ajantha Devi is working as a Research head in AP3 Solutions, Chennai, Tamil Nadu, India. She received her Ph D from University of Madras in 2015. She has worked as Project Fellow under UGC Major Research Project. She is a Senior Member of IEEE. She has been certified as “Microsoft Certified Application Developer” (MCAD) and “Microsoft Certified Technical Specialist” (MCTS) from Microsoft Corp. She has more than 40 papers in international journals and conference proceedings to her credit. She has written, co-authored, and edited a number of books in the field of Computer science with international and national publishers like Elsevier, Springer., etc. Associated as a member of the Program Committee/Technical Committee/ Chair/ Review Board for a variety of international conferences. She has five Australian Patents and one Indian Patent to her credit in the area of Artificial Intelligence, Image Processing and Medical Imaging. Her work in Image Processing, Signal Processing, Pattern Matching, and Natural Language Processing is based on artificial intelligence, machine learning, and deep learning techniques. She has won many Best paper presentation awards as well as a few research-oriented international awards.
Dr. Anand Nayyar received Ph.D (Computer Science) from Desh Bhagat University in 2017 in the area of Wireless Sensor Networks, Swarm Intelligence and Network Simulation. He is currently working in School of Computer Science-Duy Tan University, Da Nang, Vietnam as Professor, Scientist, Vice-Chairman (Research) and Director- Io T and Intelligent Systems Lab. A Certified Professional with 125+ Professional certificates from CISCO, Microsoft, Amazon, EC-Council, Oracle, Google, Beingcert, EXIN, GAQM, Cyberoam and many more. Published more than 150+ Research Papers in various High-Quality ISI-SCI/SCIE/SSCI Impact Factor Journals cum Scopus/ESCI indexed Journals, 70+ Papers in International Conferences indexed with Springer, IEEE and ACM Digital Library, 40+ Book Chapters in various SCOPUS/WEB OF SCIENCE Indexed Books with Springer, CRC Press, Wiley, IET, Elsevier with Citations: 9000+, H-Index: 50 and I-Index: 175. Member of morethan 60+ Associations as Senior and Life Member including IEEE, ACM. He has authored/co-authored cum Edited 50+ Books of Computer Science. Associated with more than 500+ International Conferences as Programme Committee/Chair/Advisory Board/Review Board member. He has 18 Australian Patents, 4 German Patents, 2 Japanese Patents, 11 Indian Design cum Utility Patents, 1 USA Patent, 3 Indian Copyrights and 2 Canadian Copyrights to his credit in the area of Wireless Communications, Artificial Intelligence, Cloud Computing, Io T and Image Processing. Awarded 39 Awards for Teaching and Research—Young Scientist, Best Scientist, Best Senior Scientist, Asia Top 50 Academicians and Researchers, Young Researcher Award, Outstanding Researcher Award, Excellence in Teaching, Best Senior Scientist Award, DTU Best Professor and Researcher Award- 2019, 2020-2021, 2022 and many more. He is listed in Top 2% Scientists as per Stanford University (2020, 2021, 2022). He has been indexed in Research.com (D-Index: 31 and Viet Nam Rank:2) in area of Computer Science. He is acting as Associate Editor for Wireless Networks (Springer), Computer Communications (Elsevier), International Journal of Sensor Networks (IJSNET) (Inderscience), Frontiers in Computer Science, Peer J Computer Science, Human Centric Computing and Information Sciences (HCIS), Tech Science Press- CSSE, IASC, IET-Quantum Communications, IET Wireless Sensor Systems, IET Networks, IJDST, IJISP, IJCINI, IJGC, IJSIR. He is acting as Editor-in-Chief of IGI-Global, USA Journal titled “International Journal of Smart Vehicles and Smart Transportation (IJSVST)”. He has reviewed more than 4000+ Articles for diverse Web of Science and Scopus Indexed Journals. He is currently researching in the area of Wireless Sensor Networks, Internet of Things, Swarm Intelligence, Cloud Computing, Artificial Intelligence, Drones, Blockchain, Cyber Security, Healthcare Informatics, Big Data and Wireless Communications.
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