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


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


Jiwen Lu

Tsinghua University

Nikolaos Boulgouris

Brunel University

Amit K. Roy-Chowdhury

University of California, Riverside


Tentative Technical Program Committee Members

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 Format & Page Limit: Same as regular paper

Submission: CMT *

*: Please choose "Human Identification in Multimedia"


(08:30 - 08:35) Opening Remarks

(08:35 – 9:10) Keynote Talk: Dr. Chen Change (Cavan) Loy, Chinese University of Hong Kong

(09:10 - 10:10) Session I – Video Analysis for Human Identification (4 papers)

ID 5: Verification-Based Pairwise Gait Identification Suibing Tong (Shanghai Jiaotong University), Yuzhuo Fu (Shanghai Jiaotong University), and Hefei Ling (Huazhong University of Science and Technology)

ID 199: Integration of Deep Features and Hand-Crafted Features for Person Re-identification Sutong Zheng (Beijing University of Posts and Telecommunications), Xiaoyu Li (Academy of Broadcasting Science), Aidong Men (Beijing University of Posts and Telecommunications), Xiaoqiang Guo (ABS), and Bo Yang (Beijing University of Posts and Telecommunications)

ID 89: Video Object Graph: A Novel Semantic Level Representation for Videos Xin Feng (Chongqing University of Technology), Yuanyi Xue (NYU Tandon School of Engineering), and Yao Wang (NYU Tandon School of Engineering)

ID 150: A Novel Object Tracker Designed Based on A Complementary Framework Shixiong Zhang (CHU HAI College of High Education) and Ah Chung Tsoi (CHU HAI College of High Education)

(10:10 – 10:30) Coffee Break

(10:30 - 11:30) Session II – Face Analysis for Human Identification (4 papers)

ID 24: Discriminative Metric Learning for Video-Based Kinship Verification Haibin Yan (Beijing University of Posts and Telecommunications)

ID 83: Robust Single-Label Classification of Facial Attributes Ahmed Mohammed (Deakin University) and Atul Sajjanhar (Deakin University)

ID 167: Facial Expression Recognition with Deep Age Zhaojie Luo (Kobe University), Jinhui Chen (Kobe University), Tetsuya Takiguchi (Kobe University) and Yasuo Ariki (Kobe University)

ID 26: Domain Transfer Sparse Representation for Single-Sample Face Recognition Venice Erin Liong (Nanyang Technological University) and Haibin Yan (Beijing University of Posts and Telecommunications)

(11:30 - 12:30) Session III – Human Identification Applications (4 papers)

ID 201: A Novel and Robust Face Clustering Method via Adaptive Difference Dictionary Jiaxiang Ren (Tongji University), Shengjie Zhao (Tongji University), Kai Yang (Tongji University) and Brian Zhao (Shanghai High School International Division)

ID 101: A Robust Object Detection: Application to Detection of Visual Knives Himanshu Buckchash (Indian Institute of Technology Roorkee) and Balasubramanian Raman (Indian Institute of Technology Roorkee)

ID 4: A Novel Framework for Video Summarization Based on Smooth Pursuit Information from Eye Tracker Data Md Musfequs Salehin (Charles Sturt University) and Manoranjan Paul (Charles Sturt University)

ID 179: A Distance Transform Based TIP Point Detection Method for Neurons in Confocal Microscopy Images Weixun Chen (Hunan University), Min Liu (Hunan University) and Rong Gong (Hunan University)

(12:30 – 12:35) Closing Remarks