A hybrid [ICP and GA] image registration algorithm for depth images

Author

Agarwal, Sankalp ; Sharma, Isha ; Anudeep Varma, D.V. ; Raj, Alex Noel Joseph

Author_Institution

SENSE, VIT Univ., Vellore, India

fYear

2014

fDate

9-9 Oct. 2014

Firstpage

8

Lastpage

14

Abstract

Iterative Closest Point (ICP) is an algorithm used to find the rotation and translation to efficiently register two point sets. A major drawback of the ICP algorithm is that it demands the data point sets to be approximately registered before it can be applied. Genetic algorithms (GA) provide a global solution to this problem and have no such prerequisite, but their convergence speed is slow. In this paper, we have demonstrated the use of a hybrid of a binary genetic algorithm (GA) and the Comprehensive ICP (CICP) algorithm (an existing variant of the ICP algorithm) to register depth images of a human face. The application of the GA followed by the CICP algorithm has proven to be fast and efficient and has no precondition on initial registration. The hybrid algorithm was able to register twenty control points to an RMS error of 0.6148 in 2.0187 seconds on an average.).

Keywords

face recognition; genetic algorithms; image registration; iterative methods; CICP algorithm; GA; binary genetic algorithm; comprehensive ICP algorithm; human face depth image registration; hybrid image registration algorithm; iterative closest point algorithm; Algorithm design and analysis; Approximation algorithms; Biological cells; Genetic algorithms; Iterative closest point algorithm; Registers; Sociology; Control points; Fitness function; Genetic algorithm; ICP algorithm; Modified Hausdorff distance; Rigid registration;

fLanguage

English

Publisher

ieee

Conference_Titel

Smart Structures and Systems (ICSSS), 2014 International Conference on

Conference_Location

Chennai

Print_ISBN

978-1-4799-6506-9

Type

conf

DOI

10.1109/ICSSS.2014.7006176

Filename

7006176