{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T16:27:49Z","timestamp":1780763269345,"version":"3.54.1"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030348687","type":"print"},{"value":"9783030348694","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-34869-4_3","type":"book-chapter","created":{"date-parts":[[2019,11,25]],"date-time":"2019-11-25T00:02:57Z","timestamp":1574640177000},"page":"22-29","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Enhanced Depression Detection from Facial Cues Using Univariate Feature Selection Techniques"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4385-0120","authenticated-orcid":false,"given":"Swati","family":"Rathi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2821-2219","authenticated-orcid":false,"given":"Baljeet","family":"Kaur","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3122-5096","authenticated-orcid":false,"given":"R. K.","family":"Agrawal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,11,25]]},"reference":[{"key":"3_CR1","unstructured":"Depression. https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/depression. Accessed 29 Apr 2019"},{"key":"3_CR2","doi-asserted-by":"publisher","unstructured":"Al Jazaery, M., Guo, G.: Video-based depression level analysis by encoding deep spatiotemporal features. IEEE Trans. Affect. Comput. (2018). https:\/\/doi.org\/10.1109\/TAFFC.2018.2870884","DOI":"10.1109\/TAFFC.2018.2870884"},{"key":"3_CR3","doi-asserted-by":"publisher","DOI":"10.1515\/9781400874668","volume-title":"Curse of Dimensionality. Adaptive Control Processes: A Guided Tour","author":"R Bellman","year":"1961","unstructured":"Bellman, R.: Curse of Dimensionality. Adaptive Control Processes: A Guided Tour. Princeton University Press, Princeton (1961)"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Cohn, J.F., et al.: Detecting depression from facial actions and vocal prosody. In: 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, pp. 1\u20137. IEEE (2009)","DOI":"10.1109\/ACII.2009.5349358"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Cummins, N., Joshi, J., Dhall, A., Sethu, V., Goecke, R., Epps, J.: Diagnosis of depression by behavioural signals: a multimodal approach. In: Proceedings of the 3rd ACM International Workshop on Audio\/Visual Emotion Challenge, pp. 11\u201320. ACM (2013)","DOI":"10.1145\/2512530.2512535"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Dibeklio\u011flu, H., Hammal, Z., Yang, Y., Cohn, J.F.: Multimodal detection of depression in clinical interviews. In: Proceedings of the 2015 ACM on International Conference on Multimodal Interaction, pp. 307\u2013310. ACM (2015)","DOI":"10.1145\/2818346.2820776"},{"issue":"02","key":"3_CR7","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1142\/S0219720005001004","volume":"3","author":"C Ding","year":"2005","unstructured":"Ding, C., Peng, H.: Minimum redundancy feature selection from microarray gene expression data. J. Bioinf. Comput. Biol. 3(02), 185\u2013205 (2005)","journal-title":"J. Bioinf. Comput. Biol."},{"key":"3_CR8","volume-title":"Pattern Classification","author":"RO Duda","year":"2012","unstructured":"Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. Wiley, Hoboken (2012)"},{"key":"3_CR9","volume-title":"What the Face Reveals: Basic and Applied Studies of Spontaneous Expression Using the Facial Action Coding System (FACS)","author":"R Ekman","year":"1997","unstructured":"Ekman, R.: What the Face Reveals: Basic and Applied Studies of Spontaneous Expression Using the Facial Action Coding System (FACS). Oxford University Press, Oxford (1997)"},{"key":"3_CR10","volume-title":"Non-Verbal Communication in Depression","author":"H Ellgring","year":"2007","unstructured":"Ellgring, H.: Non-Verbal Communication in Depression. Cambridge University Press, Cambridge (2007)"},{"issue":"Mar","key":"3_CR11","first-page":"1157","volume":"3","author":"I Guyon","year":"2003","unstructured":"Guyon, I., Elisseeff, A.: An introduction to variable and feature selection. J. Mach. Learn. Res. 3(Mar), 1157\u20131182 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Jan, A., Meng, H., Gaus, Y.F.A., Zhang, F., Turabzadeh, S.: Automatic depression scale prediction using facial expression dynamics and regression. In: Proceedings of the 4th International Workshop on Audio\/Visual Emotion Challenge, pp. 73\u201380. ACM (2014)","DOI":"10.1145\/2661806.2661812"},{"issue":"9","key":"3_CR13","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1046\/j.1525-1497.2001.016009606.x","volume":"16","author":"K Kroenke","year":"2001","unstructured":"Kroenke, K., Spitzer, R.L., Williams, J.B.: The PHQ-9: validity of a brief depression severity measure. J. Gen. Intern. Med. 16(9), 606\u2013613 (2001)","journal-title":"J. Gen. Intern. Med."},{"key":"3_CR14","volume-title":"An Approach to Environmental Psychology","author":"A Mehrabian","year":"1974","unstructured":"Mehrabian, A., Russell, J.A.: An Approach to Environmental Psychology. The MIT Press, Cambridge (1974)"},{"key":"3_CR15","doi-asserted-by":"crossref","unstructured":"Meng, H., Huang, D., Wang, H., Yang, H., Ai-Shuraifi, M., Wang, Y.: Depression recognition based on dynamic facial and vocal expression features using partial least square regression. In: Proceedings of the 3rd ACM International Workshop on Audio\/Visual Emotion Challenge, pp. 21\u201330. ACM (2013)","DOI":"10.1145\/2512530.2512532"},{"key":"3_CR16","doi-asserted-by":"crossref","unstructured":"Nasir, M., Jati, A., Shivakumar, P.G., Nallan Chakravarthula, S., Georgiou, P.: Multimodal and multiresolution depression detection from speech and facial landmark features. In: Proceedings of the 6th International Workshop on Audio\/Visual Emotion Challenge, pp. 43\u201350. ACM (2016)","DOI":"10.1145\/2988257.2988261"},{"key":"3_CR17","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1136\/jnnp-2013-306984","volume":"85","author":"D Nutt","year":"2014","unstructured":"Nutt, D.: The Hamilton depression scale- accelerator or break on antidepressant drug discovery? J. Neurol. Neurosurg. Psychiatry 85, 119\u2013120 (2014). https:\/\/doi.org\/10.1136\/jnnp-2013-306984","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"3_CR18","unstructured":"Organization, W.H., et al.: Depression and other common mental disorders: global health estimates. Technical report, World Health Organization (2017)"},{"issue":"1","key":"3_CR19","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1186\/s13640-017-0212-3","volume":"2017","author":"A Pampouchidou","year":"2017","unstructured":"Pampouchidou, A., et al.: Quantitative comparison of motion history image variants for video-based depression assessment. EURASIP J. Image Video Process. 2017(1), 64 (2017)","journal-title":"EURASIP J. Image Video Process."},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Pampouchidou, A., et al.: Depression assessment by fusing high and low level features from audio, video, and text. In: Proceedings of the 6th International Workshop on Audio\/Visual Emotion Challenge, pp. 27\u201334. ACM (2016)","DOI":"10.1145\/2988257.2988266"},{"key":"3_CR21","doi-asserted-by":"publisher","unstructured":"Pampouchidou, A., et al.: Automatic assessment of depression based on visual cues: a systematic review. IEEE Trans. Affect. Comput. (2017). https:\/\/doi.org\/10.1109\/TAFFC.2017.2724035","DOI":"10.1109\/TAFFC.2017.2724035"},{"issue":"1","key":"3_CR22","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1093\/biomet\/13.1.25","volume":"13","author":"K Pearson","year":"1920","unstructured":"Pearson, K.: Notes on the history of correlation. Biometrika 13(1), 25\u201345 (1920)","journal-title":"Biometrika"},{"key":"3_CR23","doi-asserted-by":"crossref","unstructured":"Ringeval, F., et al.: AVEC 2017: real-life depression, and affect recognition workshop and challenge. In: Proceedings of the 7th Annual Workshop on Audio\/Visual Emotion Challenge, pp. 3\u20139. ACM (2017)","DOI":"10.1145\/3133944.3133953"},{"issue":"6","key":"3_CR24","doi-asserted-by":"publisher","first-page":"1113","DOI":"10.1109\/TPAMI.2014.2366127","volume":"37","author":"E Sariyanidi","year":"2014","unstructured":"Sariyanidi, E., Gunes, H., Cavallaro, A.: Automatic analysis of facial affect: a survey of registration, representation, and recognition. IEEE Trans. Pattern Anal. Mach. Intell. 37(6), 1113\u20131133 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"3_CR25","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1093\/fampra\/cmr092","volume":"29","author":"I Schumann","year":"2011","unstructured":"Schumann, I., Schneider, A., Kantert, C., L\u00f6we, B., Linde, K.: Physicians attitudes, diagnostic process and barriers regarding depression diagnosis in primary care: a systematic review of qualitative studies. Fam. Pract. 29(3), 255\u2013263 (2011)","journal-title":"Fam. Pract."},{"key":"3_CR26","doi-asserted-by":"crossref","unstructured":"Sun, B., et al.: A random forest regression method with selected-text feature for depression assessment. In: Proceedings of the 7th Annual Workshop on Audio\/Visual Emotion Challenge, pp. 61\u201368. ACM (2017)","DOI":"10.1145\/3133944.3133951"},{"key":"3_CR27","doi-asserted-by":"crossref","unstructured":"Valstar, M., et al.: AVEC 2016: depression, mood, and emotion recognition workshop and challenge. In: Proceedings of the 6th International Workshop on Audio\/visual Emotion Challenge, pp. 3\u201310. ACM (2016)","DOI":"10.1145\/2988257.2988258"},{"key":"3_CR28","doi-asserted-by":"crossref","unstructured":"Williamson, J.R., et al.: Detecting depression using vocal, facial and semantic communication cues. In: Proceedings of the 6th International Workshop on Audio\/Visual Emotion Challenge, pp. 11\u201318. ACM (2016)","DOI":"10.1145\/2988257.2988263"},{"key":"3_CR29","doi-asserted-by":"crossref","unstructured":"Williamson, J.R., Quatieri, T.F., Helfer, B.S., Horwitz, R., Yu, B., Mehta, D.D.: Vocal biomarkers of depression based on motor incoordination. In: Proceedings of the 3rd ACM International Workshop on Audio\/Visual Emotion Challenge, pp. 41\u201348. ACM (2013)","DOI":"10.1145\/2512530.2512531"},{"key":"3_CR30","doi-asserted-by":"crossref","unstructured":"Yang, L., Jiang, D., Xia, X., Pei, E., Oveneke, M.C., Sahli, H.: Multimodal measurement of depression using deep learning models. In: Proceedings of the 7th Annual Workshop on Audio\/Visual Emotion Challenge, pp. 53\u201359. ACM (2017)","DOI":"10.1145\/3133944.3133948"},{"issue":"4","key":"3_CR31","doi-asserted-by":"publisher","first-page":"578","DOI":"10.1109\/TAFFC.2017.2650899","volume":"9","author":"Y Zhu","year":"2017","unstructured":"Zhu, Y., Shang, Y., Shao, Z., Guo, G.: Automated depression diagnosis based on deep networks to encode facial appearance and dynamics. IEEE Trans. Affect. Comput. 9(4), 578\u2013584 (2017)","journal-title":"IEEE Trans. Affect. Comput."}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Machine Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-34869-4_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,11]],"date-time":"2024-03-11T15:12:30Z","timestamp":1710169950000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-34869-4_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030348687","9783030348694"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-34869-4_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"25 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PReMI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition and Machine Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tezpur","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 December 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 December 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"premi2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.tezu.ernet.in\/~premi2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"341","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"131","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"38% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}