期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

基于局部区域稀疏编码的人脸检测 被引量：10

Face Detection Based on Local Region Sparse Coding
在线阅读 下载PDF
导出
摘要 提出一种基于局部区域稀疏编码的人脸检测方法.首先提取人脸局部区域作为训练样本;然后学习得到一个具有较强判别性的字典,字典中的每个基与人脸各局部区域有明确的对应关系;接着,基于各检测窗口稀疏编码的响应判断人脸某一局部区域是否出现;最后,利用人脸局部区域的检测结果和位置约束进行投票,完成人脸定位.该方法的创新在于将稀疏编码和基于部件模型的思想相结合,实现人脸检测.在Caltech和BioID人脸数据库的实验结果表明:该方法适用于小样本问题,且在遮挡、复杂表情、人脸偏转等情况下具有较好的检测效果. In this paper, a face detection method based on local region sparse coding is proposed. First, every local face regions are extracted as training sample. Next, a discriminative dictionary whose atoms have explicit relations with local regions is learned. Then the appearance of a particular local region is determined based on the response of its sparse coding for each detection window. Finally, face location is obtained using position constraints and detection results of local regions. The innovation of the proposed method lies in combining sparse coding and part based model for face detection. Experimental results in Caltech and BioID database show that the proposed method is suitable for small sample size problem and has good detection results in case of occlusion, rotation, complex expressions.
作者 张抒 蔡勇 解梅
机构地区 电子科技大学电子工程学院 空军工程大学信息与导航学院
出处 《软件学报》 EI CSCD 北大核心 2013年第11期2747-2757,共11页 Journal of Software
基金 国家自然科学基金(61271288) 广东省自然科学基金(8152840301000009)
关键词 人脸检测 稀疏编码 字典学习 部分模型 检测精度 召回率 face detection sparse coding dictionary learning part based model detection accuracy recall
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献21

  • 1Mairal J, Leordeanu M, Bach F, Hebert M, Ponce J. Discriminative sparse image models for class-specific edge detection and image interpretation. In: Proc. of the Computer Vision-ECCV 2008. Springer-Verlag, 2008. 43-56. [doi: 10.1007/978-3-540-88690-7 4].
  • 2Heiseleu B, Serret T, Pontils M, Poggiot T. Component-Based face detection. In: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. IEEE Computer Society Press, 2001. 657-662. [doi: 10.1109/CVPR.2001.990537].
  • 3Rowley H, Baluja S, Kanade T. Neural network-based face detection. IEEE Trans, on Pattern Analysis and Machine Intelligence, 1998,20(l):23-38. [doi: 10.1109/34.655647].
  • 4Augusteijn MF, Skujca TL. Identification of human faces through texture-based feature recognition and neural network technology. In: Proc. of the IEEE Conf. on Neural Networks. IEEE, 1993. 392-398. [doi: 10.1I09/1CNN.I993.298589].
  • 5Jiang ZL, Lin Z, Davis LS. Learning a discriminative dictionary for sparse coding via label consistent K-SVD. In: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. IEEE Computer Society Press, 2011. 1697-1704. [doi: 10.1109%2fCVP R.2011.5995354].
  • 6Liao SC, Zhu XX, Lei Z, Zhang L, Li SZ. Learning multi-scale block local binary patterns for face recognition. In: Proc. of the Int’l Conf. on Biometrics. IEEE, 2007. 828-837. [doi: 10.1007/978-3-540-74549-5 87].
  • 7Osuna E, Freund R, Girosi, F. Training support vector machines: An application to face detection. In: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. IEEE Computer Society Press, 1997. 130-136. [doi: 10.1109/CVPR.1997.609310].
  • 8Pham D, Venkatesh S. Joint learning and dictionary construction for pattern recognition. In: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. IEEE Computer Society Press, 2008. 1-8. [doi: 10.1109/CVPR.2008.4587408].
  • 9Ortiz EG, Wright A, Shah M. Face recognition in movie trailers via mean sequence sparse representation-based classification. In: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. IEEE Computer Society Press, 2013. 3531-3538. http:// ieeexplore. ieee.org/xpl/articlcDetai I s.j sp?tp^&amumber=6619297&queryText%3DFacc+rccognition+in+movie+trailers+viai~ mean +sequence+sparse+representation-based+classification.
  • 10Yang G, Huang TS. Human face detection in complex background. Pattern Recognition, 1994,27(l):53-63. [doi: 10.1016/0031 -3203(94)90017-5].

二级参考文献1

共引文献27

同被引文献62

  • 1魏良,苏光大,邓亚峰.基于FPGA的快速人脸检测[J].电子技术应用,2006,32(11):33-35. 被引量：2
  • 2Gunasekar S,Ghosh J,Bovik A.Face Detection on Distorted Images Augmented by Perceptual Quality Aware Features[J].IEEE transactions on information forensics and security,2014,9(12):2119-2131.
  • 3Usui H,Tanabe J,Sano T,et al.An evaluation of an energy efficient many-core SoC with parallelized face detection[C]//ASP-DAC.2014:311-316.
  • 4Aliradi R,Bouzera N,Meziane A,et al.Detection of Facial Components Based on SVM Classification and Invariant Feature[C]//Web Intelligence(WI)and Intelligent Agent Technologies(IAT),20131EEE/WIC/ACM International Joint Conferences on.IEEE,2013,3:30-36.
  • 5Lee K M.Component-based face detection and verification[J].Pattern Recognition Letters,2008,29(3):200-214.
  • 6Yoonseop Kang S K S C.Deep Learning to Hash with Multiple Representations[C]//IEEE International Conference on Data Mining.IEEE,2012:930-935.
  • 7Ciresan D,Meier U,Schmidhuber J.Multi-column deep neural networks for image classification[C]//Computer Vision and Pattern Recognition(CVPR),2012 IEEE Conference on.IEEE,2012:3642-3649.
  • 8Ichikawa K,Mita T,Hori O.Component-based robust face detection using AdaB oost and decision tree[C]//Automatic Face and Gesture Recognition,2006.FGR 2006.7th International Conference on.IEEE,2006:413-420.
  • 9Heisele B,Serre T,Pontil M,et al.Component-based face detection[C]//Computer Vision and Pattern Recognition,2001.CVPR 2001.Proceedings of the 2001 IEEE Computer Society Conference on.IEEE,2001,vol.1:1:I-657-I-662.
  • 10Ichikawa K,Mita T,Hori O,et al.Component-based face detection method for various types of occluded faces[C]//Communications,Control and Signal Processing,2008.ISCCSP 2008.3rd International Symposium on.IEEE,2008:538-543.

引证文献10

二级引证文献41

软件学报
2013年 第11期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部