基于交互式禁忌搜索的从阴影恢复形状算法
Improving Shape from Shading with Interactive Tabu Search
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摘要: 基于优化的从阴影恢复形状算法(SFS)对初始值敏感:初始值的误差是形状重建失败的重要因素。在本文中, 我们引入人机交互来解决该问题。本方法关键有两点。首先, 我们将SFS算法从依赖单一的初始值输入扩展到支持多组初始值输入。然后, 我们利用基于用户反馈形状重建效果的启发式的禁忌搜索, 来探索该初始值空间。该方法在合成及真实图像上的形状重建结果提供了更理想的重建效果, 展示了该方法的有效性。Abstract: 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.
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Keywords:
- shape from shading /
- user interaction /
- tabu search
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