Modeling Bayesian estimation for deformable contours
Modeling Bayesian estimation for deformable contours
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DOI：
10.1109/iccv.1999.790376
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发表时间：
1999-09
期刊：
影响因子：
--
通讯作者：
S. Li;Juwei Lu
中科院分区：
文献类型：
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作者：
S. Li;Juwei Lu
贝叶斯框架中提出了一种新颖的可训练蛇模型，称为 EigenSnake。在 EigenSnake 中，特定对象形状的先验知识（例如面部轮廓和面部特征）源自形状的训练集，并以先验分布的形式合并到贝叶斯蛇模型中。此外，基于主成分分析获得的一组特征向量构建的“形状空间”用于限制和稳定最优解的搜索。实验证明了其有效性，表明 EigenSnake 比现有模型产生更可靠、更准确的结果。
A novel trainable snake model called EigenSnake, is presented in the Bayesian framework. In the EigenSnake, prior knowledge of a specific object shape, such as that of face outlines and facial features, is derived from a training set of the shape and incorporated into a Bayesian snake model in the form of the prior distribution. Further, a "shape space", which is constructed on the basis of a set of eigenvectors obtained from principle component analysis, is used to restrict and stabilize the search for the optimal solution. The effectiveness is demonstrated by experiments, which shows that the EigenSnake produces more reliable and accurate results than existing models.