第3期 刘卓锟，等：视听觉跨模态表面材质检索 ·429· 模态信息的不断加入和特征提取的方法不断改 al[C]//Proceedings of the 19th IEEE International Confer- 进，未来该方法的应用前景必定更加广阔。 ence on Image Processing.Orlando,USA,2013:1949. 1952. 参考文献： [11]MANDAL D.BISWAS S.Generalized coupled diction- [1]MANDAL D,BISWAS S.Query specific re-ranking for ary learning approach with applications to cross-modal improved cross-modal retrieval[J].Pattern Recognition matching[J].IEEE transactions on image processing, Letters,2017,98:110-116. 2016,25(8):3826-3837. [2]WANG Kaiye,HE Ran,WANG Liang,et al.Joint feature [12]STRESE M,SCHUWERK C,IEPURE A,et al.Mul- selection and subspace learning for cross-modal retrieval timodal feature-based surface material classification[J]. [J].IEEE transactions on pattern analysis and machine in- IEEE transactions on haptics,2017,10(2):226-239. telligence,2016,38(10):2010-2023 [13]CAO Jiuwen,ZHAO Tuo,WANG Jianzhong,et al.Ex- [3]DENG Cheng,TANG Xu,YAN Junchi,et al.Discriminat- cavation equipment classification based on improved ive dictionary learning with common label alignment for MFCC features and ELM[J].Neurocomputing,2017,261: cross-modal retrieval[J].IEEE transactions on multimedia, 231-241 2016,18(2):208-218. [14]RASIWASIA N.MAHAJAN D,MAHADEVAN V,et al. [4]ZHANG Liang,MA Bingpeng,LI Guorong,et al.Metric Cluster canonical correlation analysis[Cl//Proceedings of based on multi-order spaces for cross-modal retrieval[C]// the Seventeenth International Conference on Artificial In- Proceedings of 2017 IEEE International Conference on telligence and Statistics.Reykjavik,Iceland,2014:823-831. Multimedia and Expo.Hong Kong,China,2017:1374- [15]STRESE M,BOECK Y,STEINBACH E.Content-based 1379 surface material retrieval[C]//Proceedings of 2017 IEEE [s]张毅，谢延义，罗元，等.一种语音特征提取中Ml倒谱 World Haptics Conference.Munich,Germany,2017:352-357 系数的后处理算法[J).智能系统学报，2016,11(2)： 208-215. 作者简介： ZHANG Yi,XIE Yanyi,LUO Yuan,et al.Postprocessing 刘卓锟，男，1994年生，硕士研究 method of MFCC in speech feature extraction[J].CAAI 生，主要研究方向为新型磁性材料与 transactions on intelligent systems,2016,11(2):208-215. 器件、触觉感知与模式识别。 [6]WEI Yunchao,ZHAO Yao,LU Canyi,et al.Cross-modal retrieval with CNN visual features:a new baseline[J]. IEEE transactions on cybernetics,2017.47(2):449-460. [7]RANJAN V.RASIWASIA N.JAWAHAR C V.Multi-la- bel cross-modal retrieval[C]//Proceedings of 2015 IEEE 刘华平，男.1976年生，副教授 International Conference on Computer Vision.Santiago, 博士生导师，IEEE Senior Member、中 国人工智能学会理事，中国人工智能 Chile,.2015:4094-4102 学会认知系统与信息处理专业委员会 [8]SHARMA A.KUMAR A.DAUME H.et al.Generalized 秘书长，主要研究方向为机器人感知」 multiview analysis:a discriminative latent space[C]//Pro- 学习与控制、多模态信息融合。主持 ceedings of 2012 IEEE Conference on Computer Vision 国家自然科学基金5项。发表学术论 and Pattern Recognition.Providence,USA,2012:2160- 文200余篇，被SCI检索100余篇。 2167 [9]HARDOON D R,SZEDMAK S.SHAWE-TAYLOR J. 黄文美，女，1969年生，教授，主要研 究方向为磁性材料与器件、电机及其 Canonical correlation analysis:an overview with applica- 控制技术。完成国家自然科学基金项 tion to learning methods[J].Neural Computation,2004, 目4项、河北省自然科学基金项目 16(12:2639-2664 2项。发表学术论文40余篇，被SC1、 [10]CHEN Yongming,WANG Liang,WANG Wei,et al. EI、ISTP检索20余篇。 Continuum regression for cross-modal multimedia retriev-模态信息的不断加入和特征提取的方法不断改 进，未来该方法的应用前景必定更加广阔。 参考文献： MANDAL D, BISWAS S. Query specific re-ranking for improved cross-modal retrieval[J]. Pattern Recognition Letters, 2017, 98: 110–116. [1] WANG Kaiye, HE Ran, WANG Liang, et al. Joint feature selection and subspace learning for cross-modal retrieval [J]. IEEE transactions on pattern analysis and machine in￾telligence, 2016, 38(10): 2010–2023. [2] DENG Cheng, TANG Xu, YAN Junchi, et al. Discriminat￾ive dictionary learning with common label alignment for cross-modal retrieval[J]. IEEE transactions on multimedia, 2016, 18(2): 208–218. [3] ZHANG Liang, MA Bingpeng, LI Guorong, et al. Metric based on multi-order spaces for cross-modal retrieval[C]// Proceedings of 2017 IEEE International Conference on Multimedia and Expo. Hong Kong, China, 2017: 1374- 1379. [4] 张毅, 谢延义, 罗元, 等. 一种语音特征提取中 Mel 倒谱 系数的后处理算法 [J]. 智能系统学报, 2016, 11(2): 208–215. ZHANG Yi, XIE Yanyi, LUO Yuan, et al. Postprocessing method of MFCC in speech feature extraction[J]. CAAI transactions on intelligent systems, 2016, 11(2): 208–215. [5] WEI Yunchao, ZHAO Yao, LU Canyi, et al. Cross-modal retrieval with CNN visual features: a new baseline[J]. IEEE transactions on cybernetics, 2017, 47(2): 449–460. [6] RANJAN V, RASIWASIA N, JAWAHAR C V. Multi-la￾bel cross-modal retrieval[C]//Proceedings of 2015 IEEE International Conference on Computer Vision. Santiago, Chile, 2015: 4094-4102. [7] SHARMA A, KUMAR A, DAUME H, et al. Generalized multiview analysis: a discriminative latent space[C]//Pro￾ceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA, 2012: 2160- 2167. [8] HARDOON D R, SZEDMAK S, SHAWE-TAYLOR J. Canonical correlation analysis: an overview with applica￾tion to learning methods[J]. Neural Computation, 2004, 16(12): 2639–2664. [9] CHEN Yongming, WANG Liang, WANG Wei, et al. Continuum regression for cross-modal multimedia retriev- [10] al[C]//Proceedings of the 19th IEEE International Confer￾ence on Image Processing. Orlando, USA, 2013: 1949- 1952. MANDAL D, BISWAS S. Generalized coupled diction￾ary learning approach with applications to cross-modal matching[J]. IEEE transactions on image processing, 2016, 25(8): 3826–3837. [11] STRESE M, SCHUWERK C, IEPURE A, et al. Mul￾timodal feature-based surface material classification[J]. IEEE transactions on haptics, 2017, 10(2): 226–239. [12] CAO Jiuwen, ZHAO Tuo, WANG Jianzhong, et al. Ex￾cavation equipment classification based on improved MFCC features and ELM[J]. Neurocomputing, 2017, 261: 231–241. [13] RASIWASIA N, MAHAJAN D, MAHADEVAN V, et al. Cluster canonical correlation analysis[C]//Proceedings of the Seventeenth International Conference on Artificial In￾telligence and Statistics. Reykjavik, Iceland, 2014: 823-831. [14] STRESE M, BOECK Y, STEINBACH E. Content-based surface material retrieval[C]//Proceedings of 2017 IEEE World Haptics Conference. Munich, Germany, 2017: 352-357. [15] 作者简介： 刘卓锟，男，1994 年生，硕士研究 生，主要研究方向为新型磁性材料与 器件、触觉感知与模式识别。 刘华平，男，1976 年生，副教授， 博士生导师，IEEE Senior Member、中 国人工智能学会理事，中国人工智能 学会认知系统与信息处理专业委员会 秘书长，主要研究方向为机器人感知、 学习与控制、多模态信息融合。主持 国家自然科学基金 5 项。发表学术论 文 200 余篇，被 SCI 检索 100 余篇。 黄文美,女,1969 年生,教授,主要研 究方向为磁性材料与器件、电机及其 控制技术。完成国家自然科学基金项 目 4 项、河北省自然科学基金项目 2 项。发表学术论文 40 余篇,被 SCI、 EI、ISTP 检索 20 余篇。 第 3 期 刘卓锟，等：视听觉跨模态表面材质检索 ·429·