Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
ACM Transactions on Graphics (TOG)
SMI '04 Proceedings of the Shape Modeling International 2004
Efficient 3D object retrieval using depth images
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Feature-based similarity search in 3D object databases
ACM Computing Surveys (CSUR)
An Approximate and Efficient Method for Optimal Rotation Alignment of 3D Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of content based 3D shape retrieval methods
Multimedia Tools and Applications
A GPU Based 3D Object Retrieval Approach Using Spatial Shape Information
ISM '10 Proceedings of the 2010 IEEE International Symposium on Multimedia
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
Lightweight Web3D modeling by finding and reusing repeated components
Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
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In this paper we present a new method for alignment of 3D objects. This approach is based on the exhaustive optimization search in the 3D space using GPU based genetic algorithm. The descriptor of 3D object used as the objective function to be optimized is a newly developed pose-variant similarity measure, which is obtained directly from the voxelized model's geometry and could be entirely implemented on the GPU. In order to reduce the traditional optimal algorithms' large processing time, we exploit the GPU's highly parallel architecture and transport our approach from CPU to GPU. Experimental results show that the proposed method is superior to existing normalization techniques such as PCA and provides a high degree of precision to align 3D objects.