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A Performance Evaluation of Feature Descriptors for Image Stitching in Architectural Images

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Computer Vision - ACCV 2014 Workshops (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9009))

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Abstract

We present a performance comparison of \(4\) feature descriptors for the task of feature matching in Panorama Stitching on images taken from architectural scenes and archaeological sites. Such scenes are generally characterized by structured objects that vary in their depth and large homogeneous regions. We test SIFT, LIOP, HRI and HRI-CSLTP on \(4\) different categories of images: well-structured with some depth variations, partially homogeneous with large depth variations, nearly homogeneous with a little amount of structural details and illumination-variant. These challenges test the distinctiveness and the intensity normalization schemes adopted by these descriptors. HRI-CSLTP and SIFT perform on par with each other and are better than the others on many of the test scenarios while LIOP performs well when the intensity changes are complex. The results of LIOP also show that the order computations of the pixels have to be made in a noise-resilient manner, especially in homogeneous regions.

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Notes

  1. 1.

    A region of image is well-structured when it is characterized by regular occurrences of homogeneous or textured patches that are flanked by well-defined object gradients. A typical example is that of a building, as opposed to an image of a scenery.

  2. 2.

    A region is saturated if its pixels have intensities either below \(10\) or above \(245\).

  3. 3.

    A set of images is suitable for panoramic stitching if all of them depict a planar scene or are shot with the camera center being fixed.

  4. 4.

    http://www.robots.ox.ac.uk/~vgg/research/affine/desc_evaluation.html#code.

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Authors and Affiliations

  1. Computer Vision Lab, Indian Institute of Technology Madras, Chennai, 600036, India

    Prashanth Balasubramanian, Vinay Kumar Verma & Anurag Mittal

Authors
  1. Prashanth Balasubramanian
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  2. Vinay Kumar Verma
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  3. Anurag Mittal
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Corresponding author

Correspondence to Prashanth Balasubramanian .

Editor information

Editors and Affiliations

  1. Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, India

    C.V. Jawahar

  2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

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Balasubramanian, P., Verma, V.K., Mittal, A. (2015). A Performance Evaluation of Feature Descriptors for Image Stitching in Architectural Images. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9009. Springer, Cham. https://doi.org/10.1007/978-3-319-16631-5_38

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  • DOI: https://doi.org/10.1007/978-3-319-16631-5_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16630-8

  • Online ISBN: 978-3-319-16631-5

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