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Vision Saliency Feature Extraction Based on Multi-scale Tensor Region Covariance

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Information Retrieval (CCIR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10390))

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Abstract

In the process of extracting image saliency features by using regional covariance, the low-level higher-order data are dealt with by vectorization, however, the structure of the data (color, intensity, direction) may be lost in the process, leading to a poorer representation and overall performance degradation. In this paper we introduce an approach for sparse representation of region covariance that will preserve the inherent structure of the image. This approach firstly calculates the image low-level data (color, intensity, direction), and then uses multi-scale transform to extract the multi-scale features for constructing tensor space, at last by using tensor sparse coding the image bottom features are extracted from region covariance. In the paper, it compares the experimental results with the commonly used feature extraction algorithms’ results. The experimental results show that the proposed algorithm is closer to the actual boundary of the object and achieving better results.

This work was supported in part by the National Natural Science Foundation of China under Grant 61650105, Grant 61462042, and Grant 61462045, in part by the Jiangxi Education Science and Technology Research Project under Grant GJJ160324.

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Author information

Authors and Affiliations

  1. College of Computer Information and Engineering, Jiangxi Normal University, Nanchang, 330022, China

    Shimin Wang, Mingwen Wang, Jihua Ye & Anquan Jie

Authors
  1. Shimin Wang
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  2. Mingwen Wang
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  3. Jihua Ye
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  4. Anquan Jie
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Corresponding author

Correspondence to Shimin Wang .

Editor information

Editors and Affiliations

  1. Renmin University, Beijing, China

    Jirong Wen

  2. Université de Montréal, Montreal, Canada

    Jianyun Nie

  3. East China University of Science and Technology, Shanghai, China

    Tong Ruan

  4. Tsinghua University, Beijing, China

    Yiqun Liu

  5. Wuhan University, Wuhan, Hubei, China

    Tieyun Qian

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Wang, S., Wang, M., Ye, J., Jie, A. (2017). Vision Saliency Feature Extraction Based on Multi-scale Tensor Region Covariance. In: Wen, J., Nie, J., Ruan, T., Liu, Y., Qian, T. (eds) Information Retrieval. CCIR 2017. Lecture Notes in Computer Science(), vol 10390. Springer, Cham. https://doi.org/10.1007/978-3-319-68699-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-68699-8_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68698-1

  • Online ISBN: 978-3-319-68699-8

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