用词袋模型评价体育赛事识别

Vo Dinh Phong, Tran Ngoc Trung, Le Bac
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引用次数: 0

摘要

本文利用词袋模型对体育赛事图像进行了大量的实验。为了提高基于BOW模型的朴素贝叶斯分类器的性能,我们提出了一种简单而有效的特征提取和视觉字典生成相结合的方法。尽管这不是一个新颖的想法,但我们的算法在事件识别领域提供了令人鼓舞的性能。此外,在事件图像聚类方面,该方法在一定程度上可以与典型作品相抗衡。在设计用于事件识别的特征共享框架时,涉及两个挑战数据集来发现需要关注的有趣事实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Evaluating Sport Event Recognition using Bag-of-Words Model
This paper presents extensive experiments on sport event images using the bag-of-words model. We propose a simple but effective combination of feature extraction and visual dictionary formation to boost the performance of naive Bayes classifier based on BOW model. Despite of not being a novel idea, our algorithm offers encouraging performance in event recognition domain. Moreover, in certain degrees, it can compete to typical works in event image clustering. Two challenge datasets are involved in discovering interesting facts needed to be concerned when designing a features sharing framework for event recognition.
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