On the automated interpretation and indexing of American Football
On the automated interpretation and indexing of American Football
复制标题
关于美式足球的自动解释和索引
DOI：
10.1109/mmcs.1999.779303
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
T. Caelli
中科院分区：
文献类型：
--
作者：
M. Lazarescu;S. Venkatesh;G. West;T. Caelli
将自然语言理解和图像处理与增量学习相结合，开发一个可以自动解释和索引美式足球的系统。我们已经开发了一个模型来表示在这个领域的动态场景中的多个对象的时空特性。我们的表示结合了专家知识，领域知识，空间知识和时间知识。我们还提出了一个增量学习算法，以提高知识库，以及保持以前开发的概念与新的数据一致。增量学习算法的优点是它不分裂概念，并且它生成一个不存储实例的紧凑的概念层次。
Combines natural language understanding and image processing with incremental learning to develop a system that can automatically interpret and index American Football. We have developed a model for representing spatio-temporal characteristics of multiple objects in dynamic scenes in this domain. Our representation combines expert knowledge, domain knowledge, spatial knowledge and temporal knowledge. We also present an incremental learning algorithm to improve the knowledge base as well as to keep previously developed concepts consistent with new data. The advantages of the incremental learning algorithm are that is that it does not split concepts and it generates a compact conceptual hierarchy which does not store instances.