Over the past few decades, human recognition has been extensively studied. Most of the research concentrates on typical physiological traits, e.g., face, fingerprint, voice, etc., which are usually distinctive for different individuals but difficult to semantically describe. The recent advances have aroused the emerging research in soft biometric attributes, e.g., gender, age, accent, etc., which are not necessarily unique but have semantic interpretations. Such soft biometric attribute offers middle-level characteristics of a person to bridge the gap between low-level machine features and high-level human descriptions. The produced middle-level characteristics are particularly useful in large-scale biometric identification applications, such as human-machine interaction, visual tagging/indexing, and person re-identification. Soft biometric learning and recognition from big data thus has become a very active inter-disciplinary research area, involving computer vision, machine learning and biometrics. The goal of the workshop is to disseminate recent research findings for researchers on a focused platform, foster in-depth discussion of technical solutions, identify application opportunities for large-scale soft biometrics, and explore potential collaborations.
Topics of interest include, but are not limited to:
1. Recognition on age, gender, ethnicity, hair color, etc.
2. Soft biometric feature extraction
3. Soft biometric feature evaluation
4. Soft biometric feature reduction and classification
5. Soft biometric system
6. Studying the reliability of soft biometric characteristics
7. Soft biometric information capture system
8. Databases for evaluating methods on soft biometric
9. Soft biometric security classification
10. Novel soft biometric traits
11. Fusion of primary and soft biometric information
Yongxin Ge, Chongqing University, China
Xin Feng, Chongqing University of Technology, China
Xiuzhuang Zhou, Capital Normal University, China
Li Geng,The City University of New York
Mohammad Elhoseiny, Facebook AI Lab, US
Mingchen Gao, National Institutes of Health, China
Shenghua Gao, ShanghaiTech University, China
Guodong Guo, West Virginia University, US
Junlin Hu, Nanyang Technological University, Singapore
Bo Liu, Rutgers University, US
Weitao Li, Hefei University of Technology, China
Zechao Li, Nanjing University of Science and Technology, China
Xiaoyan Luo, Beihang university, China
Xiaoming Liu, Michigan State University, US
Chuanxian Ren, Sun Yat-sen University, China
Chaoqun Weng, Nanyang Technological University, Singapore
Lu Wang, Osaka University, Japan
Xiang Yu, NEC Laboratories America Media Analytics Lab, US
Yang Yu, Facebook, US
Jianyu Yang, Soochow University, China
Jianwei Yang, Virginia Tech, US
Qijun Zhao, Sichuan University, China
Kunlei Zhang, Wayne State University, US
Yang Xiao, Huazhong University of Science and Technology, China
Half-day workshop (e.g. 9:00am~11:40pm)
6 oral presentations. Each oral presentation will be given 20 minutes including Q&A time.
Paper Submission and Review
The format of any submitted paper should follow the one for WACV2017.
This workshop will select one best paper.
Paper submission deadline: January 13, 2017January 20, 2017
Paper acceptance notification: February 3, 2017
Camera ready deadline: February 14, 2017
Workshop date: March 30, 2017
For the papers which have ever been submitted to WACV but been rejected, the authors are encouraged to submit their WACV comments by printing their WACV comments from the CMT system as PDF file and submitting this PDF file as supplementary file along with their submission to the workshop.
||Conclusions & Future Work|
· Chongqing University, China
· Address: No. 174 Shazhengjie, Shapingba, Chongqing, China, 430044
· Email: email@example.com
Yongxin Ge is currently an Associate Professor at the School of Software Engineering, Chongqing University, China. He received the B. Eng. degree in information and computing science, the M.S. degree in operations research and control theory and the Ph.D. degree in computer science and technology from the Chongqing University, Chongqing, China, in 2003, 2006 and 2011, respectively. From Sep. 2008 to Sep. 2009, he was an exchange PhD student in the department of Computer Science, University of Alberta, Canada, under the support of the China Scholarship Council. His research interests include image processing, pattern recognition and computer vision. He has published over 20 technical papers in international journals and conferences. He was a co-organizer of Special Session on “Video Analysis and Understanding”, SPIE International Conference on Visual Communication and Image Processing (VCIP), 2015.
· Chongqing University of Technology, China
· Address: No. 69,Hongguang Ave., Banan,Chongqing, China, 400054
· Email: firstname.lastname@example.org
Xin Feng is an Associate Professor at Department of Computer Science and Engineering in Chongqing University of Technology, Chongqing, China. She is currently making a two-year postdoc study at the Dept. of Electrical & Computer Engineering of New York University Tandon School of Engineering, New York, USA, under the support of the China Scholarship Council. She received the B.E. degree in computing science and technology, and the Ph.D. degree in computer application from Chongqing University, Chongqing, China, in 2004, 2011, respectively. From Sep. 2007 to Sep. 2008, she was a postgraduate exchange student in Dept. of Electrical & Computer Engineering of New York University Polytechnic School of Engineering, New York, USA. Her research interests include computer vision, video/image processing, with a particular emphasis in image/video representation and scene understanding. She has published 20 technical papers in international journals and conferences. She was a co-organizer of special session on International Conference on Visual Communication and Image Processing (VCIP), 2015.
· Capital Normal University, China
· Address: No.105, West Ring North Road, Haidian District Beijing, China, 100048
· Email: email@example.com
Xiuzhuang Zhou is currently an associate professor in College of Information Engineering, Capital Normal University, Beijing, China. He received B.S. degree from Department of Atmosphere Physics, Chengdu University of Information Technology, Chengdu, China, in 1996. He received M.E. degree and Ph.D. degree from School of Computer Science, Beijing Institute of Technology, Beijing, China, in 2005 and 2011, respectively. His research interests include computer vision, pattern recognition, and machine learning. He has published more than 40 scientific papers in peer-reviewed journals and conferences including some top venues such as the IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, IEEE Transactions on Information Forensics and Security, CVPR and ACM MM. He is an Associate Editor of the Neurocomputing.
· The City University of New York
· Address: 186 Jay Street,Brooklyn, New York, USA, 11201
· Email: LGeng@citytech.cuny.edu
Li Geng is currently an assistant professor in Department of Electrical Engineering & Telecommunication Technology at New York City College of Technology of the City University of New York. She received her B. Eng. degree in Telecommunication Engineering from Huazhong University of Science and Technology, Wuhan, China, in 2009. She received her Ph.D. degree in Electrical Engineering from Stony Brook University, New York, USA, in 2015. She has published around 10 scientific papers in peer-reviewed journals and conferences. Her research interests are in the area of statistical signal and image processing, signal detection and estimation, pattern recognition, as well as their applications to a wide area such as indoor localization and tracking with wearable sensor devices in health care systems and robotics.