A DPM based object detector using HOG-LBP features

被引：0
|
作者：
Cucliciu, Tanase [2 ]
Lin, Chih-Yang [1 ,2 ]
Muchtar, Kahlil [3 ]
机构：
[1] Yuan Ze Univ, Dept Commun Engn, Taoyuan, Taiwan
[2] Asia Univ, Dept Bioinformat & Med Engn, Taichung, Taiwan
[3] Natl Sun Yat Sen Univ, Dept Elect Engn, Kaohsiung, Taiwan
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TW) | 2017年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we combine Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP) in order to detect the cranium and its components; namely, the brain, eyes and mouth. Furthermore, Deformable Part Model (DPM) algorithm is paired with the AdaBoost for training and classification. We use a CT/PET database acquired from the National Biomedical Imaging Archive (NBIA) in order to train and test our solution.
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页数：2
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