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Accurate Overlap Area Detection Using a Histogram and Multiple Closest Points

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Computer Vision and Graphics (ICCVG 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6375))

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Abstract

In this paper, we propose a novel ICP variant that uses a histogram in conjunction with multiple closest points to detect the overlap area between range images being registered. Tentative correspondences sharing similar distances are normally all within, or all outside, the overlap area. Thus, the overlap area can be detected in a bin by bin batch manner using a histogram. Using multiple closest points is likely to enlarge the distance difference for tentative correspondences in the histogram, and pull together the images being registered, facilitating the overlap area detection. Our experimental results based on real range images show that the performance of our proposed algorithm enhances the state of the art.

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Liu, Y., Martin, R.R., Li, L., Wei, B. (2010). Accurate Overlap Area Detection Using a Histogram and Multiple Closest Points. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2010. Lecture Notes in Computer Science, vol 6375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15907-7_13

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  • DOI: https://doi.org/10.1007/978-3-642-15907-7_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15906-0

  • Online ISBN: 978-3-642-15907-7

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