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 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
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
Chu-Song Chen
Academia Sinica, Taiwan
Guoliang Fan
Oklahoma State University
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
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.
Tsinghua University
Brunel University
University of California, Riverside