Fast similar face retrieval based on mobile platform
-
摘要: 主要研究了移动平台上的相似脸检索问题.对于移动端,首先采用基于稀疏约束的级联回归模型进行精确的人脸配准,该方法不但能够筛选鲁棒的特征,而且可以将模型的大小压缩到原来的5%左右.接着,在某些关键点周围提取高维的纹理特征,并通过稀疏投影降维.对于服务器端,采用级联形状和纹理特征的方式进行高效的相似脸检索.首先基于稀疏形状重构的方式筛选脸型相似的人脸,然后基于稀疏纹理重构的方法确定相似脸.在三星Note 3智能手机上,人脸图像的配准时间约10 ms.在扩展的LFW(Labeled Face in Wild)数据库上,相似脸检索时间约1.5 s,整个模型大小约5.4 MB.大量实验结果表明,配准方法精度高,速度快,模型小;相似脸检索的方法效率高,检索结果更符合人们的视觉感受.Abstract: The problem of similar face retrieval on the mobile platform was studied. For the mobile terminal, sparse constrained cascade regression model was utilized to align the face image accurately, which could not only select the robust features, but also compress the model size to about 5% compared to the original size. Then high-dimensional texture features were extracted around some specific landmarks, and compressed by sparse projection. For the server side, shape and texture features were cascaded to retrieve similar faces efficiently. Faces with similar facial shape were selected by sparse shape reconstruction, and similar faces were finally selected by sparse texture reconstruction. On the Samsung smart phone of Note 3, the alignment time for each face image was about 10 ms. On the extended labeled face in wild (LFW) database, the retrieval time was about 1.5 s and the size of the whole model was only 5.4 MB. Extensive experiments show that the proposed alignment method is accurate and fast with compact model size. Similar face retrieval is efficient and the results are consistent with human visual perception.
-
Key words:
- mobile platform /
- face alignment /
- cascade regression /
- similar face retrieval /
- sparse constraint
-
[1] Hua G, Fu Y,Turk M,et al.Introduction to the special issue on mobile vision[J].International Journal of Computer Vision,2012,96(3):277-279. [2] 山世光, 高文,唱轶钲,等.人脸识别中的“误配准灾难”问题研究[J].计算机学报,2005,28(5):783-791. Shan S G,Gao W,Chang Y Z,et al.“Curse of Mis-alignment”problem in face recognition[J].Chinese Journal of Computers, 2005,28(5):783-791(in Chinese). [3] Cootes T F, Taylor C J,Cooper D H,et al.Active shape models-their training and application[J].Computer Vision and Image Understanding,1995,61(1):38-59. [4] Cootes T F, Edwards G J,Taylor C J.Active appearance models[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(6):681-685. [5] Cristinacce D, Cootes T.Automatic feature localisation with constrained local models[J].Pattern Recognition,2008,41(10):3054-3067. [6] Zhu X X, Ramanan D.Face detection,pose estimation,and landmark localization in the wild[C]//Proceeding of the Computer Vision and Pattern Recognition.Washington:IEEE Computer Society,2012:2879-2886. [7] Zhou F, Brandt J,Lin Z.Exemplar-based graph matching for robust facial landmark localization[C]//Proceedings of the IEEE International Conference on Computer Vision.Piscataway,NJ:IEEE,2013:1025-1032. [8] Sun Y, Wang X G,Tang X O.Deep convolutional network cascade for facial point detection[C]//Proceeding of the Computer Vision and Pattern Recognition.Washington:IEEE Computer Society,2013:3476-3483. [9] Cao X D, Wei Y C,Wen F,et al.Face alignment by explicit shape regression[C]//Proceeding of the Computer Vision and Pattern Recognition.Washington:IEEE Computer Society,2012:2887-2894. [10] Xiong X H, De la Torre F.Supervised descent method and its applications to face alignment[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Washington:IEEE Computer Society,2013:532- 539. [11] Ren S Q, Cao X D,Wei Y C,et al.Face alignment at 3000 FPS via regressing local binary features[C]//Proceeding of the Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE,2014:1232-1240. [12] Burgos-Artizzu X P,Perona P,Dollar P.Robust face landmark estimation under occlusion[C]//Proceeding of the International Conference on Computer Vision.Piscataway,NJ:IEEE,2013:1513-1520. [13] Chen D, Cao X,Wen F,et al.Blessing of dimensionality:high-dimensional feature and its efficient compression for face verification[C]//Proceeding of the Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE,2013:3025-3032. [14] Gionis A, Indyk P,Motwani R.Similarity search in high dimensions via hashing[J].VLDB,1999,99(6):518-529. [15] Huang G B, Mattar M,Berg T,et al.Labeled faces in the wild:a database for studying face recognition in unconstrained environments[J].International Journal of Computer Vision,2007,96(3):277-279. [16] Asthana A, Zafeiriou S,Cheng S,et al.Robust discriminative response map fitting with constrained local models[C]//Proceeding of the Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE,2013:3444-3451. [17] Tibshirani R. Regression shrinkage and selection via the lasso[J].Journal of the Royal Statistical Society,1996,24(3):267-288. [18] Sagonas C, Tzimiropoulos G,Zafeiriou S,et al.300 faces in-the-wild challenge:the first facial landmark localization challenge[C]//Proceedings of the IEEE International Conference on Computer Vision.Piscataway,NJ:IEEE,2013:397-403. [19] Yan J J, Zhang X C,Lei Z,et al.Structural models for face detection[C]//Proceeding of the Automatic Face and Gesture Recognition.Washington:IEEE Computer Society,2013:1-6. [20] Cheng J, Leng C,Wu J X,et al.Fast and accurate image matching with cascade hashing for 3D reconstruction[C]//Proceeding of the Computer Vision and Pattern Recognition.Piscataway,NJ:IEEE,2014:1-8.
点击查看大图
计量
- 文章访问数: 1061
- HTML全文浏览量: 25
- PDF下载量: 773
- 被引次数: 0