Title :
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
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;
Conference_Titel :
Smart Structures and Systems (ICSSS), 2014 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-6506-9
DOI :
10.1109/ICSSS.2014.7006176