Natural Language Person Retrieval

Authors

  • Tao Zhou University of California, Los Angeles
  • Jie Yu SAIC Innovation Center

DOI:

https://doi.org/10.1609/aaai.v31i1.11083

Keywords:

person retrieval, LSTM, CNN, batch normalization, max pooling

Abstract

Following the recent progress in image classification and image captioning using deep learning, we developed a novel person retrieval system using natural language, which to our knowledge is first of its kind. Our system employs a state-of-the-art deep learning based natural language object retrieval framework to detect and retrieve people in images. Quantitative experimental results show significant improvement over state-of-the-art meth- ods for generic object retrieval. This line of research provides great advantages for searching large amounts of video surveil- lance footage and it can also be utilized in other domains, such as human-robot interaction.

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Published

2017-02-12

How to Cite

Zhou, T., & Yu, J. (2017). Natural Language Person Retrieval. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.11083