Invited Talk

Invited Talk : Video summarization: visual surveillance and medical imaging.

posted Aug 2, 2021, 6:17 PM by SangHyun Seo   [ updated Aug 23, 2021, 12:18 AM by Sang-Soo Yeo ]


Dr. Irfan Mehmood
Assistant Professor, School of Media, Desing and Technology, 
University of Bradford, UK

 Irfan Mehmood has been involved in IT industry and academia in Pakistan, South Korea, and UK for over 10 years. He is now serving as a Assistant Professor in Applied Artificial Intelligence, Faculty of Engineering & Informatics, School of Media, Design and Technology, University of Bradford, UK. His sustained contribution at various research and industry-collaborative projects give him an extra edge to meet the current challenges faced in the field of multimedia analytics, information mining and summarization. Specifically, he has made significant contribution in the areas of visual surveillance, information mining and data encryption. He has published 90+ papers in peer-reviewed international journals and conferences such as Information Fusion, Neurocomputing, IEEE Access, IEEE Transactions on Industrial Informatics, IEEE Internet of Things Journal, International Journal of Information Management, Future Generation Computer Systems, Sensors, Journal of Visual Communication and Image Representation, Multimedia Tools and Applications, Computers in Human Behaviour, EURASIP Journal on Image and Video Processing, Mobile Networks and Applications, Computers in Biology and Medicine, Journal of Medical Systems, Signal, Image and Video Processing, Bio-Medical Materials and Engineering, KSII Transactions on Internet and Information Systems, NBIS 2015, MITA 2015, PlatCon 2016, SKIMA 2019, and IWFCV 2020. He is serving as a professional reviewer for numerous well-reputed journals such as Journal of Visual Communication and Image Representation, Future Generation Computer Systems, IEEE Access, Journal of Super Computing, Signal Image and Video Processing, Multimedia Tools and Applications, ACM Transactions on Embedded Computing Systems, and Enterprise Information Systems. He acted as GE/LGE in several special issues of SCI/SCIE indexed journals and is currently involved in editing of several other special issues.

Abstract of Irfan Mehmood's Talk

 In recent years, there has been a tremendous increase in video capturing devices, which led to large personal and corporate digital video archives. This huge volume of video data became a source of inspiration for the development of vast numbers of applications such as visual surveillance, multimedia recommender systems, and context-aware advertising. The heterogeneity of video data, higher storage, processing cost, and communication requirements demand for a system that can efficiently manage and store huge amount of video data, while providing user-friendly access to stored data at the same time. To address this problem, video summarization schemes have been proposed. Video summarization refers to the extraction of keyframes, identifying most important and pertinent content. For instance, gastroenterologist uses wireless capsule endoscopy video technology to diagnose his patients. However, during capsule endoscopy process, video data are produced in huge amounts, but only a limited amount of data is actually useful for diagnosis. In this talk, we will explore two different aspects of video summarization: visual surveillance and medical imaging. 


Invited Talk: Multi-Component Nonnegative Matrix Factorization for Data Clustering

posted Aug 2, 2021, 6:12 PM by SangHyun Seo   [ updated Aug 23, 2021, 11:44 PM by Sang-Soo Yeo ]

Prof. Feng Tian
Dr.  Feng Tian
Professor, Bournemouth University, UK
  Dr Feng Tian is currently a professor in Bournemouth University, UK. With expertise on digital media, image processing and machine learning, Dr Tian has published over 100 papers or book chapters in peer-reviewed journals or international conferences, including IEEE Transactions on Visualization and Computer Graphics, ACM Transactions on Modelling and Computer Simulation, IEEE Transactions on Cybernetics, Visual Computer, Computer & Graphics, Multimedia Tools & Applications, International Joint Conference on Artificial Intelligence (IJCAI), Association for the Advancement of Artificial Intelligence (AAAI), Pacific Graphics (PG), IJCNN, CASA, CGI, etc. Before coming to the UK, Dr Tian worked as a post-doctoral fellow and assistant professor in Nanyang Technological University, Singapore. Dr Tian has also been awarded with research grants from Singapore National Research Foundation (Singapore), Royal Society (UK), British Art Council (UK), Horizon 2020 (EU), etc.

Abstract of Feng Tian's Talk

  A good data representation can typically reveal the latent structure of data and facilitate further processes such as clustering, classification and recognition. Nonnegative matrix factorization (NMF) as a fundamental approach for data representation has attracted great attentions. Despite its great performance, traditional NMF fails to explore the semantic information of multiple components as well as the diversity among them, which would be of great benefit to understand data comprehensively and in depth. In fact, real data are usually complex and contain various components. For example, face images have ex-pressions and genders. Each component mainly reflects one aspect of data and provides information others do not have. In this talk, I will present an approach on multi-component nonnegative matrix factorization (MCNMF). Instead of seeking only one representation of data, MCNMF learns multiple representations simultaneously, where each representation corresponds to a component. By integrating the multiple representations, a more comprehensive representation is then established.



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