Granular Video Computing : With Rough Sets, Deep Learning and in Iot

This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training.

This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing.

Debarati B Chakraborty is a young faculty associate in the Department of Computer Science and Engineering at Indian Institute of technology, Jodhpur, India. She obtained her PhD from Jadavpur University, Kolkata, India in 2017, M. Tech from National Institute of Technology, Rourkela in 2010 and B. Tech from West Bengal University of Technology in 2008. She has conducted research work towards her PhD at the Center for Soft Computing Research in Indian Statistical Institute from 2011–2017. She carried out her post-doctoral research at the same institute from 2017–2019. Her research interests include video processing, rough sets, granular computing, soft computing, artificial intelligence, machine learning, deep learning, and the Internet of Things. She received the prestigious young scientist award by Indian Science Congress Association in 2012.

Sankar K Pal is currently a National Science Chair, SERB-DST, Government of India. He is a Distinguished Scientist and former Director of the Indian Statistical Institute, a former INSA-Distinguished Professor, and a former INAE-Chair Professor. He founded the Machine Intelligence Unit and the Center for Soft Computing Research in the Institute in Calcutta. He received his PhD in Radio Physics and Electronics from Calcutta University in 1979, and another PhD in Electrical Engineering along with DIC from Imperial College, London in 1982.

He worked at the UC, Berkeley and the UMD, College Park in 1986–87; the JSC, Houston, TX in 1990–94; and in the US Naval Research Laboratory, Washington DC in 2004. Since 1997, he is a Distinguished Visitor of IEEE Computer Society, and has held several visiting positions in Italy, Poland, Hong Kong and Australia.

Prof. Pal is a Fellow of IEEE, TWAS, IAPR, IFSA, IRSS, and all four National Academies for Science/Engineering in India. He is a co-author of twenty books and 400+ research publications in the areas of pattern recognition, machine learning, image/video processing, data mining, web intelligence, soft computing, bioinformatics, and cognitive machines.

His major awards/honors include: S S Bhatnagar Prize, Padma Shri by the President of India, Khwarizmi International Award from the President of Iran, NASA Tech Brief Award (USA), Jawaharlal Nehru Fellowship, IEEE-Neural Networks Outstanding Paper Award, G D Birla Award, Om Bhasin Award, FICCI Award, ISC-P C Mahalanobis Birth Centenary Gold Medal from the Prime Minister of India, J C Bose National Fellowship, INAE-S N Mitra Award, INSA-Jawaharlal Nehru Birth Centenary Lecture, INSA Distinguished Professorial Chair, and National Science Chair, Govt. of India.

He serves (ed) on the editorial boards of 20 journals including several IEEE Transactions. He has visited 45 countries as a keynote/invited speaker/academic visitor.