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Definition
Iterative closest point (ICP) is a popular algorithm employed to register two sets of curves, two sets of surfaces, or two clouds of points.
Background
The ICP technique was proposed independently by Besl and McKay [1] and Zhang [2] in two different contexts. Besl and McKay [1] developed the ICP algorithm to register partially sensed data from rigid objects with an ideal geometric model, prior to shape inspection. So this is a subset–set matching problem because each sensed point has a correspondence in the ideal model. Zhang [2] developed the ICP algorithm in the context of autonomous vehicle navigation in rugged terrain based on vision. His algorithm is used to register a sequence of sensed data in order to build a complete model of the scene and to plan a free path for navigation. So this is a subset–subset matching problem because a fraction of data in one set does not have any correspondence in the other set. To address this issue, Zhang’s ICP algorithm...
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References
Besl PJ, McKay ND (1992) A method for registration of 3-d shapes. IEEE Trans Pattern Anal Mach Intell 14(2):239–256
Zhang Z (1994) Iterative point matching for registration of free-form curves and surfaces. Int J Comput Vis 13(2):119–152. Also Research Report No.1658, INRIA Sophia-Antipolis, 1992
Chen Y, Medioni G (1992) Object modelling by registration of multiple range images. Image Vis Comput 10(3):145–155
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Zhang, Z. (2014). Iterative Closest Point (ICP). In: Ikeuchi, K. (eds) Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-31439-6_179
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DOI: https://doi.org/10.1007/978-0-387-31439-6_179
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