中文摘要：

发现在二幅图象之间的可靠的相应的点是在计算机视觉的一个基本问题，特别与 L 视觉框架的发展。这篇论文介绍歧管的通讯并且建议一个新奇计划由听说向上的看法拒绝孤立点歧管。建议计划独立于在出版工作要估计并且克服可得到的方法的下列限制的参量的模型：效率严厉地因孤立点百分比的增加和估计的模型参数的数字倒下；孤立点拒绝被结合模型选择和模型评价。真实图象对的实验显示出我们的建议计划的优秀性能。

英文摘要：

Finding reliable corresponding points between two images is a fundamental problem in computer vision, especially with the development of L∞ vision framework. This paper introduce the correspondence manifold and propose a novel scheme to reject outliers by learning upward views of the manifold. The proposed scheme is independent of the parametric model to be estimated and overcomes the following limitations of the available methods in the published works： efficiency sharply goes down with the increase of outlier percentage and the number of the estimated model parameters; outlier rejecting is coupled with model selection and model estimation. Experiments on real image pairs show the excellent performance of our proposed scheme.