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Volume 29 Issue 5
September  2014
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Zhi-Neng Chen, Chong-Wah Ngo, Wei Zhang, Juan Cao, Yu-Gang Jiang. Name-Face Association in Web Videos: A Large-Scale Dataset, Baselines, and Open Issues[J]. Journal of Computer Science and Technology, 2014, 29(5): 785-798. DOI: 10.1007/s11390-014-1468-z
Citation: Zhi-Neng Chen, Chong-Wah Ngo, Wei Zhang, Juan Cao, Yu-Gang Jiang. Name-Face Association in Web Videos: A Large-Scale Dataset, Baselines, and Open Issues[J]. Journal of Computer Science and Technology, 2014, 29(5): 785-798. DOI: 10.1007/s11390-014-1468-z
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Name-Face Association in Web Videos: A Large-Scale Dataset, Baselines, and Open Issues

  • 1. Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;
    2. Department of Computer Science, City University of Hong Kong, Hong Kong, China;
    3. Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;
    4. School of Computer Science, Fudan University, Shanghai 200433, China

Funds: This work was supported by a research grant from City University of Hong Kong under Grant No. 7008178, and the National Natural Science Foundation of China under Grant Nos. 61228205, 61303175 and 61172153.
More Information
  • Author Bio:

    Zhi-Neng Chen received his B.S. and M.S. degrees in computerscience from the College of Information Engineering, Xiangtan University, China, in 2004 and 2007, respectively, and Ph.D. degree in computerscience from the Institute of Computing Technology, Chinese Academy ofSciences, Beijing, in 2012. He is currently an assistant professor of theInstitute of Automation, Chinese Academy of Sciences, Beijing. He was a senior research associate with the Department of Computer Science, City University of Hong Kong,in 2012. His current research interests include large-scalemultimedia information retrieval and video processing.

  • Received Date: February 23, 2014
  • Revised Date: July 02, 2014
  • Published Date: September 04, 2014
    Abstract
  • Associating faces appearing in Web videos with names presented in the surrounding context is an important task in many applications. However, the problem is not well investigated particularly under large-scale realistic scenario, mainly due to the scarcity of dataset constructed in such circumstance. In this paper, we introduce a Web video dataset of celebrities, named WebV-Cele, for name-face association. The dataset consists of 75,073 Internet videos of over 4,000 hours, covering 2,427 celebrities and 649,001 faces. This is to our knowledge the most comprehensive dataset for this problem. We describe the details of dataset construction, discuss several interesting findings by analyzing this dataset like celebrity community discovery, and provide experimental results of name-face association using five existing techniques. We also outline important and challenging research problems that could be investigated in the future.
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