A new constrained parameter estimator for computer vision applications
A new constrained parameter estimator for computer vision applications
复制标题
用于计算机视觉应用的新型约束参数估计器
DOI：
10.1016/s0262-8856(03)00140-9
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
D. Gawley
中科院分区：
文献类型：
--
作者：
W. Chojnacki;M. Brooks;A. Hengel;D. Gawley
针对一类计算机视觉问题，提出了一种约束参数估计方法。在典型应用中，参数将描述图像特征位置之间的关系，以连接参数和图像数据的方程表示，并将满足不涉及图像数据的辅助约束。该方法的一个显著特征是，它以一种集成的方式处理辅助约束，而不是通过对无约束最小化结果操作的校正过程。通过基础矩阵计算实验对该方法进行了验证。给出了合成图像和真实图像的结果。结果表明，该方法产生的结果与以前的方法相当，甚至优于以前的方法，并且具有比同类技术更快的优势。
A method of constrained parameter estimation is proposed for a class of computer vision problems. In a typical application, the parameters will describe a relationship between image feature locations, expressed as an equation linking the parameters and the image data, and will satisfy an ancillary constraint not involving the image data. A salient feature of the method is that it handles the ancillary constraint in an integrated fashion, not by means of a correction process operating upon results of unconstrained minimisation. The method is evaluated through experiments in fundamental matrix computation. Results are given for both synthetic and real images. It is demonstrated that the method produces results commensurate with, or superior to, previous approaches, with the advantage of being faster than comparable techniques.