{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T20:21:12Z","timestamp":1768508472252,"version":"3.49.0"},"reference-count":83,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,6,30]],"date-time":"2019-06-30T00:00:00Z","timestamp":1561852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Accurate face segmentation strongly benefits the human face image analysis problem. In this paper we propose a unified framework for face image analysis through end-to-end semantic face segmentation. The proposed framework contains a set of stack components for face understanding, which includes head pose estimation, age classification, and gender recognition. A manually labeled face data-set is used for training the Conditional Random Fields (CRFs) based segmentation model. A multi-class face segmentation framework developed through CRFs segments a facial image into six parts. The probabilistic classification strategy is used, and probability maps are generated for each class. The probability maps are used as features descriptors and a Random Decision Forest (RDF) classifier is modeled for each task (head pose, age, and gender). We assess the performance of the proposed framework on several data-sets and report better results as compared to the previously reported results.<\/jats:p>","DOI":"10.3390\/e21070647","type":"journal-article","created":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T03:23:59Z","timestamp":1561951439000},"page":"647","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["A Unified Framework for Head Pose, Age and Gender Classification through End-to-End Face Segmentation"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0864-5255","authenticated-orcid":false,"given":"Khalil","family":"Khan","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, University of Azad Jammu and Kashmir, Muzafarabbad 13100, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7237-180X","authenticated-orcid":false,"given":"Muhammad","family":"Attique","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, Sejong University, Seoul 05006, Korea"}]},{"given":"Ikram","family":"Syed","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, University of Azad Jammu and Kashmir, Muzafarabbad 13100, Pakistan"}]},{"given":"Ghulam","family":"Sarwar","sequence":"additional","affiliation":[{"name":"Department of Software Engineering, University of Azad Jammu and Kashmir, Muzafarabbad 13100, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3442-0727","authenticated-orcid":false,"given":"Muhammad Abeer","family":"Irfan","sequence":"additional","affiliation":[{"name":"Dipartimento di Elettronica e Telecomunicazioni (DET), Politecnico di Torino, 10156 Torino, Italy"}]},{"given":"Rehan Ullah","family":"Khan","sequence":"additional","affiliation":[{"name":"IT Department, College of Computer, Qassim University, Al-Mulida 51431, Saudi Arabia"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Asthana, A., Zafeiriou, S., Cheng, S., and Pantic, M. 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