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A novel 3D reconstruction algorithm based on hybrid immune particle swarm optimization

机译:基于混合免疫粒子群算法的新型3D重建算法

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Shape from shading (SFS) is an important method for such fields as surface measurement of an object. In order to improve the SFS 3D reconstruction accuracy, utilizing the fact that artificial immune optimization and particle swarm optimization algorithms can compensate for each other, a reconstruction method based on a hybrid immune particle swarm optimization algorithm is proposed in this paper. The design and implementation of this hybrid algorithm is discussed in detail. A synthetic vase and a scene image are used to test the validation of the proposed method, and a comparison is made. Experiment results show that the proposed method can achieve higher accuracy and is also faster.
机译:阴影形状(SFS)是用于诸如对象的表面测量之类的领域的重要方法。为了提高SFS 3D重建精度,利用人工免疫优化和粒子群算法可以相互补偿的事实,提出了一种基于混合免疫粒子群优化算法的重建方法。详细讨论了该混合算法的设计和实现。使用合成花瓶和场景图像来测试所提出方法的有效性,并进行比较。实验结果表明,该方法可以达到较高的精度,并且速度更快。

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