A comparative study of state-of-the-art evolutionary image registration methods for 3D modeling

Santamaría, José; Cordón, Óscar; Damas, Sergio

doi:10.1016/j.cviu.2011.05.006

Cited by 81 publications

(34 citation statements)

References 68 publications

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“…The most recent ones consider the use of laser range scanners to achieve a digital model of the human skull found (see Fig. 1) by means of a manual (Hee-Kyung et al 2006) or automatic 3D reconstruction procedure (Santamaría et al 2007(Santamaría et al , 2009a(Santamaría et al , 2010, as it is the case in the current contribution.…”

Section: Introductionmentioning

confidence: 96%

A cooperative coevolutionary approach dealing with the skull–face overlay uncertainty in forensic identification by craniofacial superimposition

Ibáñez

Cordón

2011

Soft Comput

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Craniofacial superimposition is a forensic process where photographs or video shots of a missing person are compared with the skull that is found. By projecting both photographs on top of each other (or, even better, matching a scanned three-dimensional skull model against the face photo/video shot), the forensic anthropologist can try to establish whether that is the same person. The whole process is influenced by inherent uncertainty mainly because two objects of different nature (a skull and a face) are involved. In previous work, we categorized the different sources of uncertainty and introduced the use of imprecise landmarks to tackle most of them. In this paper, we propose a novel approach, a cooperative coevolutionary algorithm, to deal with the use of imprecise cephalometric landmarks in the skull-face overlay process, the main task in craniofacial superimposition. Following this approach we are able to look for both the best projection parameters and the best landmark locations at the same time. Coevolutionary skull-face overlay results are compared with our previous fuzzy-evolutionary automatic method. Six skullface overlay problem instances corresponding to three realworld cases solved by the Physical Anthropology Lab at the University of Granada (Spain) are considered. Promising results have been achieved, dramatically reducing the run time while improving the accuracy and robustness.

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Section: Introductionmentioning

confidence: 96%

A cooperative coevolutionary approach dealing with the skull–face overlay uncertainty in forensic identification by craniofacial superimposition

Ibáñez

Cordón

2011

Soft Comput

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“…Literature [15] proposes to use surface interpenetration measure (SIM) as the fitness function which is more robust based on genetic algorithms, and uses hill climbing algorithm to accelerate, which improves the result. Literature [16] summarizes and analyzed the similarities and differences among varieties of genetic algorithms, and compares them with the ICP algorithm. These methods are good at dealing with complex nonlinear problems and effectively avoid the local minimum and carry on multi view registration.…”

Section: The Methods Based On Genetic Algorithmmentioning

confidence: 99%

A Review of Fine Registration for 3D Point Clouds

Xian¹,

Xiao²,

Wang

et al. 2016

Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science

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Abstract. 3D registration is an essential step in 3D reconstruction of real objects. In this paper, the fine registration methods for point clouds are classified systematically and analyzed theoretically. For several typical fine registration algorithms, experimental comparisons are also carried out on the effect of sampling parameters, iterations, iterative threshold and random noise. Furthermore, the stability and efficiency of the algorithms are tested. Based on the experimental results, the problems in current registration methods and the prospects of future research directions are also presented.

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“…Santamaria et al [10] present a more detailed overview of evolutionary methods for image registration and some state-of-the-art methods.…”

Section: Related Workmentioning

confidence: 99%

Image Registration of Very Large Images via Genetic Programming

Chicotay

David

Netanyahu

2014

2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops

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A comparative study of state-of-the-art evolutionary image registration methods for 3D modeling

Cited by 81 publications

References 68 publications

A cooperative coevolutionary approach dealing with the skull–face overlay uncertainty in forensic identification by craniofacial superimposition

A cooperative coevolutionary approach dealing with the skull–face overlay uncertainty in forensic identification by craniofacial superimposition

A Review of Fine Registration for 3D Point Clouds

Image Registration of Very Large Images via Genetic Programming

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