Improving Shape from Shading with Interactive Tabu Search
Improving Shape from Shading with Interactive Tabu Search
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DOI：
10.1007/s11390-016-1639-1
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发表时间：
2016-05
影响因子：
0.7
通讯作者：
Jing Wu;Paul L. Rosin;Xianfang Sun;Ralph Robert Martin
中科院分区：
文献类型：
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作者：
Jing Wu;Paul L. Rosin;Xianfang Sun;Ralph Robert Martin
基于阴影的形状优化（SFS）对初始化很敏感：初始化中的错误是导致整体形状重建不良的重要原因。在本文中，我们提出了一种通过用户交互来帮助克服这个问题的方法。在我们的方法中有两个关键元素。首先，我们扩展SFS以考虑一组初始化，而不是使用单个初始化。其次，在用户评价重构质量的指导下，采用启发式搜索方法禁忌搜索对初始化空间进行有效的搜索；在合成图像和真实图像上的重建结果都证明了我们的方法在提供更理想的形状重建方面的有效性。
Optimisation based shape from shading (SFS) is sensitive to initialization: errors in initialization are a significant cause of poor overall shape reconstruction. In this paper, we present a method to help overcome this problem by means of user interaction. There are two key elements in our method. Firstly, we extend SFS to consider a set of initializations, rather than to use a single one. Secondly, we efficiently explore this initialization space using a heuristic search method, tabu search, guided by user evaluation of the reconstruction quality. Reconstruction results on both synthetic and real images demonstrate the effectiveness of our method in providing more desirable shape reconstructions.