Locality preserving hashing

Yi Hsuan Tsai; Ming Hsuan Yang

doi:10.1109/ICIP.2014.7025604

Locality preserving hashing

Yi Hsuan Tsai, Ming Hsuan Yang

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

The spectral hashing algorithm relaxes and solves an objective function for generating hash codes such that data similarity is preserved in the Hamming space. However, the assumption of uniform global data distribution limits its applicability. In the paper, we introduce locality preserving projection to determine the data distribution adaptively, and a spectral method is adopted to estimate the eigenfunctions of the underlying graph Laplacian. Furthermore, pairwise label similarity can be further incorporated in the weight matrix to bridge the semantic gap between data and hash codes. Experiments on three benchmark datasets show the proposed algorithm performs favorably against state-of-the-art hashing methods.

Original language	English
Title of host publication	2014 IEEE International Conference on Image Processing, ICIP 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2988-2992
Number of pages	5
ISBN (Electronic)	9781479957514
DOIs	https://doi.org/10.1109/ICIP.2014.7025604
Publication status	Published - 2014 Jan 28

Publication series

Name	2014 IEEE International Conference on Image Processing, ICIP 2014

All Science Journal Classification (ASJC) codes

Computer Vision and Pattern Recognition

Access to Document

10.1109/ICIP.2014.7025604

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Tsai, Y. H., & Yang, M. H. (2014). Locality preserving hashing. In 2014 IEEE International Conference on Image Processing, ICIP 2014 (pp. 2988-2992). [7025604] (2014 IEEE International Conference on Image Processing, ICIP 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIP.2014.7025604

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Locality preserving hashing. / Tsai, Yi Hsuan; Yang, Ming Hsuan.

2014 IEEE International Conference on Image Processing, ICIP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2988-2992 7025604 (2014 IEEE International Conference on Image Processing, ICIP 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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