Spatio-temporal feature classifier

被引：0

作者：

Wang, Yun ^{[1
]}

Liu, Suxing ^{[2
]}

机构：

[1] School of Mechanical and Electrical Engineering, Xingxiang University, Henan, Xinxiang

[2] Henan Electronic Commerce Association, Zhengzhou, 450004, Henan Province

来源：

Open Automation and Control Systems Journal | 2015年 / 7卷 / 01期

关键词：

Classifier; Feature extraction; Spatio-temporal;

D O I：

10.2174/1874444301507010001

中图分类号：

学科分类号：

摘要：

Different from current foreground and background segmentation methods, we did not utilize the low level image representation method (such as boundaries and textures) to extract the feature of the videos, instead we proposed a spatio-temporal feature classifier to obtain the union region of object from natural videos as the interest points. We slide the temporal chunk along time axis to obtain samples from videos, and train the Support Vector Machine (SVM) with feature vectors. Then we built a spatio-temporal feature classifier and tested our algorithm on the most popular benchmark dataset. Experiment results showed the effectiveness and robustness of the algorithm. © Wang and Liu

引用

页码：1 / 7

页数：6

共 11 条

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