Performance evaluation of 3D local surface descriptors for low and high resolution range image registration

    Research output: Chapter in Book/Conference paperConference paper

    11 Citations (Scopus)

    Abstract

    © 2014 IEEE. Despite the advent and popularity of low-cost commercial sensors (e.g., Microsoft Kinect), research in 3D vision still primarily focuses on the development of advanced algorithms geared towards high resolution data. This paper presents a comparative performance evaluation of renowned state-of-the-art 3D local surface descriptors for the task of registration of both high and low resolution range image data. The datasets used in these experiments are the renowned high resolution Stanford 3D models dataset and challenging low resolution Washington RGB-D object dataset. Experimental results show that the performance of certain local surface descriptors is significantly affected by low resolution data.
    Original languageEnglish
    Title of host publication2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages1-7
    VolumeN/A
    ISBN (Print)9781479954094
    DOIs
    Publication statusPublished - 2014
    Event2014 International Conference on Digital lmage Computing: Techniques and Applications (DlCTA) - Wollongong, Australia
    Duration: 25 Nov 201427 Nov 2014

    Conference

    Conference2014 International Conference on Digital lmage Computing: Techniques and Applications (DlCTA)
    Abbreviated titleDICTA 2014
    CountryAustralia
    CityWollongong
    Period25/11/1427/11/14

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    Image registration
    Sensors
    Costs
    Experiments

    Cite this

    Shah, S. A. A., Bennamoun, M., & Boussaïd, F. (2014). Performance evaluation of 3D local surface descriptors for low and high resolution range image registration. In 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA) (Vol. N/A, pp. 1-7). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/DICTA.2014.7008123
    Shah, S.A.A. ; Bennamoun, Mohammed ; Boussaïd, Farid. / Performance evaluation of 3D local surface descriptors for low and high resolution range image registration. 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA). Vol. N/A IEEE, Institute of Electrical and Electronics Engineers, 2014. pp. 1-7
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    author = "S.A.A. Shah and Mohammed Bennamoun and Farid Boussa{\"i}d",
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    doi = "10.1109/DICTA.2014.7008123",
    language = "English",
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    Shah, SAA, Bennamoun, M & Boussaïd, F 2014, Performance evaluation of 3D local surface descriptors for low and high resolution range image registration. in 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA). vol. N/A, IEEE, Institute of Electrical and Electronics Engineers, pp. 1-7, 2014 International Conference on Digital lmage Computing: Techniques and Applications (DlCTA), Wollongong, Australia, 25/11/14. https://doi.org/10.1109/DICTA.2014.7008123

    Performance evaluation of 3D local surface descriptors for low and high resolution range image registration. / Shah, S.A.A.; Bennamoun, Mohammed; Boussaïd, Farid.

    2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA). Vol. N/A IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 1-7.

    Research output: Chapter in Book/Conference paperConference paper

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    N2 - © 2014 IEEE. Despite the advent and popularity of low-cost commercial sensors (e.g., Microsoft Kinect), research in 3D vision still primarily focuses on the development of advanced algorithms geared towards high resolution data. This paper presents a comparative performance evaluation of renowned state-of-the-art 3D local surface descriptors for the task of registration of both high and low resolution range image data. The datasets used in these experiments are the renowned high resolution Stanford 3D models dataset and challenging low resolution Washington RGB-D object dataset. Experimental results show that the performance of certain local surface descriptors is significantly affected by low resolution data.

    AB - © 2014 IEEE. Despite the advent and popularity of low-cost commercial sensors (e.g., Microsoft Kinect), research in 3D vision still primarily focuses on the development of advanced algorithms geared towards high resolution data. This paper presents a comparative performance evaluation of renowned state-of-the-art 3D local surface descriptors for the task of registration of both high and low resolution range image data. The datasets used in these experiments are the renowned high resolution Stanford 3D models dataset and challenging low resolution Washington RGB-D object dataset. Experimental results show that the performance of certain local surface descriptors is significantly affected by low resolution data.

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    EP - 7

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    Shah SAA, Bennamoun M, Boussaïd F. Performance evaluation of 3D local surface descriptors for low and high resolution range image registration. In 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA). Vol. N/A. IEEE, Institute of Electrical and Electronics Engineers. 2014. p. 1-7 https://doi.org/10.1109/DICTA.2014.7008123