Center for Medical Image Science and Visualization (CMIV) and the Department of Medical and Health Sciences (IMH), Linköping University, Linköping, Sweden.
IEEE Trans Pattern Anal Mach Intell. 2011 Nov;33(11):2215-28. doi: 10.1109/TPAMI.2011.23.
This paper proposes two alternative formulations to reduce the high computational complexity of tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. The first scheme consists of numerical approximations of the votes, which have been derived from an in-depth analysis of the plate and ball voting processes. The second scheme simplifies the formulation while keeping the same perceptual meaning of the original tensor voting: The stick tensor voting and the stick component of the plate tensor voting must reinforce surfaceness, the plate components of both the plate and ball tensor voting must boost curveness, whereas junctionness must be strengthened by the ball component of the ball tensor voting. Two new parameters have been proposed for the second formulation in order to control the potentially conflictive influence of the stick component of the plate vote and the ball component of the ball vote. Results show that the proposed formulations can be used in applications where efficiency is an issue since they have a complexity of order O(1). Moreover, the second proposed formulation has been shown to be more appropriate than the original tensor voting for estimating saliencies by appropriately setting the two new parameters.
本文提出了两种替代的公式化方法来降低张量投票的高计算复杂度，张量投票是一种用于从噪声数据中提取显著信息的稳健感知分组技术。第一种方案由投票的数值逼近组成，这些数值逼近是从板和球投票过程的深入分析中得出的。第二种方案简化了公式，同时保持了原始张量投票的相同感知意义：棒张量投票和板张量投票的棒分量必须增强表面性，板和球张量投票的板分量必须增强弯曲度，而结必须由球张量投票的球分量加强。为第二种方案提出了两个新的参数，以便控制板投票的棒分量和球投票的球分量的潜在冲突影响。结果表明，所提出的公式可以用于效率是一个问题的应用中，因为它们的复杂度为 O(1)。此外，通过适当设置两个新参数，第二个提出的方案已被证明比原始张量投票更适合于估计显著度。
