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DSLIC: A Superpixel Based Segmentation Algorithm for Depth Image

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Computer Vision – ACCV 2016 Workshops (ACCV 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10117))

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Abstract

Limited illumination outdoor and indoor environment leads to the lack of object’s color information. Faced with this situation, it is not always possible to generate superpixel by using RGB or LaB features. To tackle this scenario, we propose a superpixel generation algorithm solely on depth image. We aim the semantically-incoherent superpixel problem on depth image, caused by identical depth value in the vicinity of the border. Our algorithm is an adaptation of Simple Linear Iterative Clustering (SLIC) with a novel utilization of depth and gradient direction as an alternate of LaB color space features. Our novel approach is demonstrated perform favorably to over-segment large planar area in an unlit environment.

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Authors and Affiliations

  1. Department of Information Technology on Human and Environmental Science, Kumamoto University, Kumamoto, Japan

    Ali Suryaperdana Agoes, Zhencheng Hu & Nobutomo Matsunaga

Authors
  1. Ali Suryaperdana Agoes
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  2. Zhencheng Hu
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  3. Nobutomo Matsunaga
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Corresponding author

Correspondence to Ali Suryaperdana Agoes .

Editor information

Editors and Affiliations

  1. Institute of Information Science, Academia Sinica, Taipei, Taiwan

    Chu-Song Chen

  2. Tsinghua University, Beijing, China

    Jiwen Lu

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Kai-Kuang Ma

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Agoes, A.S., Hu, Z., Matsunaga, N. (2017). DSLIC: A Superpixel Based Segmentation Algorithm for Depth Image. In: Chen, CS., Lu, J., Ma, KK. (eds) Computer Vision – ACCV 2016 Workshops. ACCV 2016. Lecture Notes in Computer Science(), vol 10117. Springer, Cham. https://doi.org/10.1007/978-3-319-54427-4_6

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  • DOI: https://doi.org/10.1007/978-3-319-54427-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54426-7

  • Online ISBN: 978-3-319-54427-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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