{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:10:47Z","timestamp":1750306247308,"version":"3.41.0"},"reference-count":49,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2017,9,4]],"date-time":"2017-09-04T00:00:00Z","timestamp":1504483200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"crossref","award":["2014A030313688"],"award-info":[{"award-number":["2014A030313688"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"crossref"}]},{"name":"External Cooperation Program of BIC, the Chinese Academy of Sciences","award":["172644KYSB20160033"],"award-info":[{"award-number":["172644KYSB20160033"]}]},{"name":"Australian Research Council Projects","award":["FT-130101457, DP-140102164 and LP-150100671"],"award-info":[{"award-number":["FT-130101457, DP-140102164 and LP-150100671"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2018,1,31]]},"abstract":"<jats:p>\n            Automatic age estimation is an important yet challenging problem. It has many promising applications in social media. Of the existing age estimation algorithms, the personalized approaches are among the most popular ones. However, most person-specific approaches rely heavily on the availability of training images across different ages for a single subject, which is usually difficult to satisfy in practical application of age estimation. To address this limitation, we first propose a new model called\n            <jats:italic>Orthogonal Gaussian Process<\/jats:italic>\n            (OGP), which is not restricted by the number of training samples per person. In addition, without sacrifice of discriminative power, OGP is much more computationally efficient than the standard Gaussian Process. Based on OGP, we then develop an effective age estimation approach, namely anisotropic OGP (A-OGP), to further reduce the estimation error. A-OGP is based on an anisotropic noise level learning scheme that contributes to better age estimation performance. To finally optimize the performance of age estimation, we propose a multifeature A-OGP fusion framework that uses multiple features combined with a random sampling method in the feature space. Extensive experiments on several public domain face aging datasets (FG-NET, MORPH Album1, and MORPH Album 2) are conducted to demonstrate the state-of-the-art estimation accuracy of our new algorithms.\n          <\/jats:p>","DOI":"10.1145\/3090311","type":"journal-article","created":{"date-parts":[[2017,9,5]],"date-time":"2017-09-05T12:23:34Z","timestamp":1504614214000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Multifeature Anisotropic Orthogonal Gaussian Process for Automatic Age Estimation"],"prefix":"10.1145","volume":"9","author":[{"given":"Zhifeng","family":"Li","sequence":"first","affiliation":[{"name":"Chinese Academy of Sciences, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dihong","family":"Gong","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Zhu","sequence":"additional","affiliation":[{"name":"Chinese University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7225-5449","authenticated-orcid":false,"given":"Dacheng","family":"Tao","sequence":"additional","affiliation":[{"name":"University of Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuelong","family":"Li","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Shaanxi, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,9,4]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168752.2168759"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2387379"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995437"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2015.2420374"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2013.2286265"},{"key":"e_1_2_1_6_1","volume-title":"Retrieved","author":"Aging Database FG-NET","year":"2015","unstructured":"FG-NET Aging Database . 2015 . FG-NET Aging Database . Retrieved July 17, 2017, from http:\/\/www-prima.inrialpes.fr\/FGnet\/html\/benchmarks.html. FG-NET Aging Database. 2015. FG-NET Aging Database. Retrieved July 17, 2017, from http:\/\/www-prima.inrialpes.fr\/FGnet\/html\/benchmarks.html."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168752.2168755"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.36"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2008.921847"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2007.4284917"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2006.877398"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2009.4959721"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1459359.1459469"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2007.70733"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2008.924280"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2010.5543609"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995404"},{"key":"e_1_2_1_18_1","volume-title":"Proceedings of the 2009 IEEE 12th International Conference on Computer Vision. IEEE","author":"Guo Guodong","year":"2009","unstructured":"Guodong Guo , Guowang Mu , Yun Fu , Charles Dyer , and Thomas Huang . 2009 b. A study on automatic age estimation using a large database . In Proceedings of the 2009 IEEE 12th International Conference on Computer Vision. IEEE , Los Alamitos, CA , 1986--1991. Guodong Guo, Guowang Mu, Yun Fu, Charles Dyer, and Thomas Huang. 2009b. A study on automatic age estimation using a large database. In Proceedings of the 2009 IEEE 12th International Conference on Computer Vision. IEEE, Los Alamitos, CA, 1986--1991."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206681"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2362759"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.1990.572934"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.709601"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2009.2017606"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/6046.825791"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2003.817091"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.993553"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2010.5543813"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2807705"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2011.2156787"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/2733383"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2015.2462732"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2010.5544598"},{"volume-title":"Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR\u201909)","author":"Mu Guowang","key":"e_1_2_1_34_1","unstructured":"Guowang Mu , Guodong Guo , Yun Fu , and Thomas S. Huang . 2009. Human age estimation using bio-inspired features . In Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR\u201909) . IEEE, Los Alamitos, CA, 112--119. Guowang Mu, Guodong Guo, Yun Fu, and Thomas S. Huang. 2009. Human age estimation using bio-inspired features. In Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR\u201909). IEEE, Los Alamitos, CA, 112--119."},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2011.2167317"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/FGR.2006.78"},{"key":"e_1_2_1_37_1","first-page":"337","article-title":"Warped Gaussian Processes","volume":"16","author":"Snelson Edward","year":"2004","unstructured":"Edward Snelson , Carl Edward Rasmussen , and Zoubin Ghahramani . 2004 . Warped Gaussian Processes . Advances in Neural Information Processing Systems 16 , 337 -- 344 . 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Huang . 2008. Regression from patch-kernel . In Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR\u201908) . IEEE, Los Alamitos, CA, 1--8. Shuicheng Yan, Xi Zhou, Ming Liu, Mark Hasegawa-Johnson, and Thomas S. Huang. 2008. Regression from patch-kernel. In Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR\u201908). IEEE, Los Alamitos, CA, 1--8."},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.5244\/C.29.55"},{"volume-title":"Proceedings of the 2004 12th Asian Conference on Computer Vision (ACCV\u201914)","author":"Yi D.","key":"e_1_2_1_47_1","unstructured":"D. Yi , Z. Lei , and S. Z. Li . 2014. Age estimation by multi-scale convolutional network . In Proceedings of the 2004 12th Asian Conference on Computer Vision (ACCV\u201914) . IEEE, Los Alamitos, CA. D. Yi, Z. Lei, and S. Z. Li. 2014. Age estimation by multi-scale convolutional network. In Proceedings of the 2004 12th Asian Conference on Computer Vision (ACCV\u201914). IEEE, Los Alamitos, CA."},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539975"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2655020"}],"container-title":["ACM Transactions on Intelligent Systems and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3090311","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3090311","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:23:47Z","timestamp":1750220627000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3090311"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,4]]},"references-count":49,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,1,31]]}},"alternative-id":["10.1145\/3090311"],"URL":"https:\/\/doi.org\/10.1145\/3090311","relation":{},"ISSN":["2157-6904","2157-6912"],"issn-type":[{"type":"print","value":"2157-6904"},{"type":"electronic","value":"2157-6912"}],"subject":[],"published":{"date-parts":[[2017,9,4]]},"assertion":[{"value":"2015-12-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2017-04-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2017-09-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}