A Center Surround Contrast Based Feature for Object Pose Estimation

被引:0
|
作者
Lim, John [1 ]
机构
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore
来源
2014 13TH INTERNATIONAL CONFERENCE ON CONTROL AUTOMATION ROBOTICS & VISION (ICARCV) | 2014年
关键词
biologically inspired feature; feature descriptor; pose estimation;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We propose a primary visual cortex inspired oriented edge feature for object pose estimation. The neural feedback like feature is based on a Center-Surround Contrast excitation and a k-Winner-Take-All inhibition, to extract different orientations of edge response from an image patch. To compute local descriptor, we model each oriented edge response with a PDF distribution, before concatenating their attributes from all orientations. To choose a suitable PDF candidate during training, we ran a similarity test fit between empirical and parametric statistics. We train a bank of binary view pose classifiers using SVM on dense features with Spatial Pyramid Representation [15]. We evaluate and compare the Mean Average Precision of our proposed descriptor with HOG [6] for pose estimation evaluation. Lastly, we showed that using our proposed feature over baseline resulted in a gain of nearly 15% on the EPFL Multi-View Car Dataset [2].
引用
收藏
页码:1033 / 1038
页数:6
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