MEMBER, IEEE, Image Processing Institute, University of Southern California, Los Angeles, CA 90007; INRIA, Rocquencourt, France; University of Paris XI, Paris, France.
IEEE Trans Pattern Anal Mach Intell. 1981 Apr;3(4):412-24. doi: 10.1109/tpami.1981.4767127.
We approach the problem of labeling a set of objects from a quantitative standpoint. We define a world model in terms of transition probabilities and propose a definition of a class of global criteria that combine both ambiguity and consistency. A projected gradient algorithm is developed to minimize the criterion. We show that the minimization procedure can be implemented in a highly parallel manner. Results are shown on several examples and comparisons are made with relaxation labeling techniques.
我们从定量的角度来处理一组对象的标注问题。我们根据转移概率定义了一个世界模型，并提出了一类同时考虑模糊性和一致性的全局准则的定义。我们开发了一个投影梯度算法来最小化这个准则。我们表明，这个最小化过程可以以高度并行的方式实现。我们在几个例子上展示了结果，并与松弛标注技术进行了比较。
