دورية أكاديمية
Commercial Video Evaluation via Low-Level Feature Extraction and Selection
العنوان: | Commercial Video Evaluation via Low-Level Feature Extraction and Selection |
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المؤلفون: | Xiangmin Lun, Mingxuan Wang, Zhenglin Yu, Yimin Hou |
المصدر: | Advances in Multimedia, Vol 2018 (2018) |
بيانات النشر: | Hindawi Limited, 2018. |
سنة النشر: | 2018 |
المجموعة: | LCC:Electronic computers. Computer science |
مصطلحات موضوعية: | Electronic computers. Computer science, QA75.5-76.95 |
الوصف: | To discover the influence of the commercial videos’ low-level features on the popularity of the videos, the feature selection method should be used to get the video features influencing the videos’ evaluation mostly after analyzing the source data and the audiences’ evaluations of the videos. After extracting the low-level features of the videos, this paper improved the Correlation-Based Feature Selection (CFS) method which is widely used and proposed an algorithm named CFS-Spearmen which combined the Spearmen correlation coefficient and the classical CFS to select features. The 4 datasets in UCI machine learning database were employed as the experiment data. The experiment results were compared with the results using traditional CFS, Minimum Redundancy and Maximum Relevance (mRMR). The SVM was used to test the method in this paper. Finally, the proposed method was used in commercial videos’ feature selection and the most influential feature set was obtained. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 1687-5680 1687-5699 |
Relation: | https://doaj.org/toc/1687-5680; https://doaj.org/toc/1687-5699 |
DOI: | 10.1155/2018/2056381 |
URL الوصول: | https://doaj.org/article/aca2c23187c94433bbf36c27ece6eb43 |
رقم الأكسشن: | edsdoj.2c23187c94433bbf36c27ece6eb43 |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 16875680 16875699 |
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DOI: | 10.1155/2018/2056381 |