The Second Workshop on Human Identification in Multimedia (HIM'17)

Abstract

Human Identities are an important information source in many high-level multimedia analysis tasks such as video summarization, semantic retrieval, interaction indexing, and scene understanding. The aim of this workshop is to bring together researchers in computer vision and multimedia to share ideas and propose solutions on how to address the many open issues in human identification, and present new datasets that introduce new challenges in the field. Human identification in multimedia is one relatively new problem in multimedia analysis and, recently, it has attracted the attention of many researchers in the field. Human Identification is significant to many multimedia related applications such as video surveillance, video search, human-computer interaction, and video summarization. Recent advances in feature representations, modeling, and inference techniques have led to a significant progress in the field. The proposed workshop aims to explore recent progress in human identification with multimedia data by taking stock of the past five years of work in this field and evaluating different algorithms. The proposed workshop will help the community to understand the challenges and opportunities of human identification in multimedia techniques for the next few years.


Topics of Interests

Topics of interest include, but are not limited to:

Multimedia feature representation
1.Image feature representation
2.Video feature representation
3.Audio feature representation
4.Multiview feature representation
5.Multimodal feature representation

Statistical learning for human identification
1.Sparse learning for human identification
2.Dictionary learning for human identification
3.Manifold learning for human identification
4.Metric learning for human identification
5.Deep learning for human identification

Applications
1.Video surveillance
2.Multimedia search
3.Video summarization
4.Benchmark datasets
5.Comparative evaluations


Relevance and Significance

This workshop aims to address recent advances in human identification with multimedia by extending the ICME conference. It focuses on developing new algorithms, systems, applications, and standards human identification in multimedia which can be applied across video and audio domains. This workshop will cover all aspects on multimedia data generated by broadcast media such as TV and Radio as well as user-generated content such as Youtube and Vimeo. The goal of the workshop is to bring together researchers and practitioners in both industry and academia to discuss the latest advance, challenges and unaddressed problems in human identification across multimedia domains as well as exchange views, ideas in related technologies and applications, in which we attempt to advance the state-of-the-art of human identification techniques.

Target Audience

This workshop is beneficial to faculties, researchers, PhD students, MS students, and engineers who are working on related topics, e.g., distance metric learning, subspace learning, manifold learning, dimensionality reduction, deep learning and their applications to various applications of human identification in multimedia. We expect there will be 60-80 people to attend this workshop. Workshop History: If accepted, the proposed workshop will be part of ICME for the second time. The first one was organized in ICME’14, where around 30 papers were submitted to this workshop and half of them were accepted and presented. There were also four invited talks in the workshop, and more than 50 persons attended this workshop.

Workshop History

If accepted, the proposed workshop will be part of ICME for the second time. The first one was organized in ICME’14, where around 30 papers were submitted to this workshop and half of them were accepted and presented. There were also four invited talks in the workshop, and more than 50 persons attended this workshop.

Committee

Key Organizers


Dr. Jiwen Lu (Contact Person) Department of Automation Tsinghua University, China
Dr. Nikolaos Boulgouris Department of Electronic & Computer Engineering Brunel University London, United Kingdom
Dr. Amit K. Roy-Chowdhury Dept. of Electrical and Computer Engineering University of California, Riverside

Tentative Technical Program Committee Members (unconfirmed)


Chu-Song Chen, Academia Sinica, Taiwan
Guoliang Fan, Oklahoma State University, USA
Yun Fu, Northeastern University, USA
Ajay Kumar, Hong Kong Polytechnic University, Hong Kong
Chia-Wen Lin, National Tsing Hua University, Taiwan
Nixon Mark, University of Southampton, UK
Ajmal S. Mian, The University of Western Australia, Australia
Pierre Moulin, University of Illinois at Urbana-Champaign, USA
Fatih Porikli, Australian National University, Australia
Ruiping Wang, Chinese Academy of Sciences, China
Xiaogang Wang, Chinese University of Hong Kong, Hong Kong
Killian Q. Weinberger, Cornell University, USA

Duration

This workshop will be a full-day workshop

7 oral presentations. Each oral presentation will be given 20 minutes including Q&A time.

1 Invited Talk, 30 minutes(if funds are available).

Submission

Paper Submission and Review
Site：TBA


The format of any submitted paper should follow the one for ICME2017.
30-40 submissions are expected to be received for this workshop, where around 50% of them will be accepted for presentation in the workshop. Each paper will be reviewed by at least 3 reviewers. The organisers will also arrange two invited talks at this workshop, which are to be confirmed soon.

Paper submission deadline: TBA
Reviewing period: TBA
Decision notification: TBA
Camera ready: TBA
Workshop day: 10 or 14 July 2017

For the papers which have ever been submitted to ICME but been rejected, the authors are encouraged to submit their ICME comments by printing their ICME comments from the CMT system as PDF file and submitting this PDF file as supplementary file along with their submission to the workshop.

Schedule

08:35
 Opening Remarks
08:40
 Invited Talk
09:10
 Paper 1
09:30
 Paper 2
09:50
 Paper 3
10:10
 Coffee Break
10:30
 Paper 4
10:50
 Paper 5
11:10
 Paper 6
11:30
 Pager 7
11:50
 Conclusions & Future Work
12:00
 Lunch


CV of organizers

Jiwen Lu, Ph.D. (Contact Person)

· Department of Automation Tsinghua University, China
· Email: lujiwen@tsinghua.edu.cn
. Homepage: http://ivg.au.tsinghua.edu.cn/Jiwen_Lu/
· Biography:
Jiwen Lu is currently an Associate Professor with the Department of Automation, Tsinghua University, China. His research interests include computer vision, pattern recognition, machine learning, and multimedia analysis. He has authored/co-authored over 140 scientific papers in these areas, where 33 papers are published in the IEEE Transactions journals such as TPAMI, TIP, and TCSVT, and 20 papers are published in the top-tier computer vision conferences such as CVPR, ICCV and ECCV. He serves as an Associate Editor of Pattern Recognition Letters, Neurocomputing, and IEEE Access, a Leading Guest Editor of two Special Issues in the Pattern recognition and Image and Vision Computing, a Guest Editor of two other Special Issue in Computer Vision and Image Understanding and Neurocomputing, a Workshop Co-Chair of WACV 2017 and ACCV 2016, a Special Session Co-Chair of VCIP 2015, a Publicity Chair of IJCB 2017, an Area Chair of WACV 2016, BTAS 2016, ICB 2016, ICME 2015, VCIP 2015, and ICB 2015, a TPC member for over 20 international conferences such as ICCV, CVPR, ECCV, ICME and ICASSP, and a reviewer for over 40 international journals such as TPAMI, TIP and TCSVT. He organized several workshops/competitions at some international conferences such as FG 2015, ACCV 2014, ICME2014, and IJCB2014. He was a recipient of the Best Student Paper Award from Pattern Recognition and Machine Intelligence Association of Singapore in 2012, the Top 10% Best Paper Award from IEEE International Workshop on Multimedia Signal Processing in 2014, and the National 1000 Young Talents Plan Program in 2015, respectively. He is a senior member of the IEEE.

 

Nikolaos Boulgouris, Ph.D

· Department of Electronic & Computer Engineering Brunel University London, United Kingdom
. E-mail: nikolaos.boulgouris@brunel.ac.uk
. Homepage: http://people.brunel.ac.uk/~eestnnb/
· Biography:
Nikolaos Boulgouris is a Senior Lecturer with the Department of Electronic and Computer Engineering of Brunel University London in the United Kingdom. He joined Brunel in September 2010. Between December 2004 and August 2010 he was an academic member of staff at King's College London. Prior to that, he was a Post-Doctoral Fellow with the Department of Electrical and Computer Engineering of the University of Toronto, Canada. Dr Boulgouris received the Ph.D. degree from the Electrical and Computer Engineering department of the University of Thessaloniki, Greece, 2002. His research interests are in the areas of pattern recognition for biometric/biomedical signals, image/video analysis and understanding, and multimedia communications. He was Principal Investigator for the UK group in the EC-funded Project ACTIBIO. He has published over 90 papers in international journals and conferences and his papers have been cited widely in papers by other researchers who work in the same research areas. Dr Boulgouris is Technical Program Co-Chair for IEEE ICIP 2018 and Publications Chair for IEEE ICASSP 2021. He is also on the organizing committee of IEEE MMSP 2017. He has been a member of the IEEE IVMSP Technical Committee since 2014. He currently serves as Senior Area Editor for the IEEE Trans. on Image Processing and the IEEE Trans. on Circuits & Systems for Video Technology. In the past he served as Associate Editor for the IEEE Transactions on Image Processing (2010-2014) and the IEEE Signal Processing Letters (2007-2010). He was co-editor of the book Biometrics: Theory, Methods, and Applications, which was published by Wiley - IEEE Press in 2009, and guest co-editor for two journal special issues on Biometrics. Dr Boulgouris is a Senior Member of the IEEE and a Fellow of UK’s Higher Education Academy..

 

Amit K. Roy-Chowdhury, Ph.D.

· Dept. of Electrical and Computer Engineering University of California, Riverside
· Email: amitrc@ece.ucr.edu
. Homepage: http://www.ee.ucr.edu/~amitrc/AmitRoyChowdhury.php
· Biography:
Amit Roy-Chowdhury leads the Video Computing Group at the University of California, Riverside (UCR) with research interests in computer vision, image processing, pattern recognition, and statistical signal processing. Dr. Roy-Chowdhury received his PhD from the University of Maryland, College Park in Electrical and Computer Engineering in 2002 and joined UCR in 2004 where he is currently a Professor of Electrical and Computer Engineering and a Cooperating Faculty in the department of Computer Science and Engineering. He has had research collaborations with or consulted with a number of private companies. His group is involved in research projects related to camera networks, human behavior modeling, media forensics, face recognition, and bioimage analysis. Prof. Roy-Chowdhury's research has been supported by various agencies including the National Science Foundation, the US Dept. of Defense, IARPA, National Endowment for the Humanities, and private industries like Google, NVDIA, CISCO, and Lockheed-Martin. His research group has published over 150 papers in peer-reviewed journals and top conferences, including over 40 journal papers and another 28 in highly competitive computer vision conferences (with acceptance rates of ~25%). He is the first author of the book Camera Networks: The Acquisition and Analysis of Videos Over Wide Areas, the first monograph on the topic. His work on face recognition in art was featured widely in the news media, including a PBS/National Geographic documentary and in The Economist. He is an Associate Editor of the IEEE Trans. on Image Processing, IEEE Trans. on Circuits and Systems in Video Technology, and Computer Vision and Image Understanding, and an Area Chair for CVPR2017. He has also served in editorial boards of other journals in the past and been on conference organizing committees.

Contact

jiwen Lu


Department of Automation Tsinghua University China

lujiwen@tsinghua.edu.cn