Best Viewpoint Selection for 3D Visualization Using Particle Swarm Optimization

doi:10.16182/j.issn1004731x.joss.201710020

Abstract

Abstract: The viewpoint selection is to automatically select one or more approximate optimal viewpoints in the viewpoints of multiple views, at the same time, it is related to the evaluation of the quality of the viewpoint. 3D visualization best viewpoint selection method based on particle swarm optimization algorithm was proposed. The viewpoint quality was evaluated by using the image information entropy and the image edge entropy, and the viewpoint was selected by the multi-objective intelligent optimization method. The basic flow begins with the initial viewpoint set, finding the best viewpoint by means of coding, particle evaluation, and particle update, which is a process of multiple iterations until a satisfactory viewpoint is found or the iterations are maximized. Experiments show that the method is effective and can automatically select the best viewpoint, which can effectively reduce the number of artificial test selection.

Key words: 3D visualization, viewpoint selection, Particle Swarm Optimization, multi-objective optimization

CLC Number:

TP391.9

Jia Panpan, Zeng Yanyang, Feng Yunxia. Best Viewpoint Selection for 3D Visualization Using Particle Swarm Optimization[J]. Journal of System Simulation, 2017, 29(10): 2384-2390.

References

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