A hybrid [ICP and GA] image registration algorithm for depth images
- Resource Type
- Conference
- Authors
- Agarwal, Sagar; Sharma, Ishan; Anudeep Varma, D. V.; Joseph Raj, Alex Noel
- Source
- 2014 International Conference on Smart Structures and Systems (ICSSS) Smart Structures and Systems (ICSSS), 2014 International Conference on. :8-14 Oct, 2014
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Iterative closest point algorithm
Genetic algorithms
Algorithm design and analysis
Registers
Biological cells
Approximation algorithms
Sociology
Rigid registration
Control points
ICP algorithm
Genetic algorithm
Modified Hausdorff distance
Fitness function
- Language
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.)