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Hashing for Face Search

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Computer Vision

Synonyms

Binary coding for face retrieval

Definition

Hashing is the process of compressing a given input real-valued feature representation into a binary code of a relatively small number of bits. For the application of face search with deep features, it corresponds to encoding a feature extracted from a deep learning-based face recognition model into a binary representation with the goal of maintaining most of the retrieval ability of the original representation.

Background

The state-of-the-art face recognition methods represent a face image as a high-dimensional real-valued feature, obtained using a deep network. However, comparisons of this high-dimensional feature can be computationally expensive. Furthermore, when dealing with large face images database, this representation can lead to prohibitive storage requirements. Thus, the goal of hashing for face search is mainly to:

  • Lower the memory consumption: hashing is a way to produce a compact representation, and thus a larger face...

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References

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Karaman, S., Chang, SF. (2020). Hashing for Face Search. In: Computer Vision. Springer, Cham. https://doi.org/10.1007/978-3-030-03243-2_817-1

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  • DOI: https://doi.org/10.1007/978-3-030-03243-2_817-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03243-2

  • Online ISBN: 978-3-030-03243-2

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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