How accurate is forensic facial identification of surgically altered faces?

References

• Feldstein S. The global expansion of AI surveillance Carnegie endowment for international peace; 2019 [cited 2020 Jun 15]. Available from: https://carnegieendowment.org/2019/09/17/global-expansion-of-ai-surveillance-pub-79847
   Google Scholar
• Jacquet M, Champod C. Automated face recognition in forensic science: review and perspectives. Forensic Sci Int. 2020;307:110–124. doi:10.1016/j.forsciint.2019.110124.
   Web of Science ®Google Scholar
• Leipner A, Obertová Z, Wermuth M, Thali M, Ottiker T, Sieberth T. 3D mug shot-3D head models from photogrammetry for forensic identification. Forensic Sci Int. 2019;300:6–12. doi:10.1016/j.forsciint.2019.04.015.
   PubMed Web of Science ®Google Scholar
• Steinthal G. 3D hand-held surveillance and real time multimodal recognition device. Final technical report, Rev. 1.1. Award No. 2009-IJ-CX-K001; 2015 [accessed 2020 Mar 3]. https://www.ncjrs.gov/pdffiles1/nij/grants/249535.pdf
   Google Scholar
• [cited 2020 Mar 3]. Available from: http://stereovisioninc.com/
   Google Scholar
• Jin H, Wang X, Zhong Z, Hua J. Robust 3D face modeling and reconstruction from frontal and side images, Comput. Computer Aided Geometric Design. 2017;50:1–13. doi:10.1016/j.cagd.2016.11.001.
   Web of Science ®Google Scholar
• Chen Y, Wu F, Wang Z, Song Y, Ling Y, Bao L. Self-supervised learning of detailed 3D face reconstruction. IEEE Trans Image Process. 2020;29:8696–8705. doi:10.1109/TIP.2020.3017347.
   Web of Science ®Google Scholar
• Zeng D, Zhao Q, Long S, Li J. Exemplar coherent 3D face reconstruction from forensic mugshot database. Image Vis Comput. 2017;58:193–203. doi:10.1016/j.imavis.2016.03.001.
   Web of Science ®Google Scholar
• Feng Z-H, Huber P, Kittler J, Hancock P, Wu X, Zhao Q, Koppen P, Rätsch M. Evaluation of dense 3D reconstruction from 2D face images in the wild. 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018); 2018:780–786.
   Google Scholar
• Eliášová H, Dostálová T, Procházka A, Šedivá E, Horáček M, Urbanová P, Hliňáková P. Comparison of 2D OPG image versus Orthopantomogram from 3D CBCT from the forensic point of view. Leg Med. 2021;48. doi:10.1016/j.legalmed.2020.101802.
   Web of Science ®Google Scholar
• Martos R, Valsecchi A, Ibáñez O, Alemán I. Estimation of 2D to 3D dimensions and proportionality indices for facial examination. Forensic Sci Int. 2018;287:142–152. doi:10.1016/j.forsciint.2018.03.037.
   PubMed Web of Science ®Google Scholar
• Gupta S, Markey MK, Bovik AC. Anthropometric 3D face recognition. Int J Comput Vis. 2010;90(3):331–349. doi:10.1007/s11263-010-0360-8.
   Web of Science ®Google Scholar
• Bowyer KW, Chang K, Flynn P. A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition. Comput Vis Image Underst. 2006;101(1):1–15. doi:10.1016/j.cviu.2005.05.005.
   Web of Science ®Google Scholar
• Smeets D, Claes P, Vandermeulen D, Clement JG. Objective 3D face recognition: evolution, approaches and challenges. Forensic Sci Int. 2010;201(1–3):125–132. doi:10.1016/j.forsciint.2010.03.023.
   PubMed Web of Science ®Google Scholar
• Abate AF, Nappi M, Riccio D, Sabatino G. 2D and 3D face recognition: a survey. Pattern Recognit Lett. 2007;28(14):1885–1906. doi:10.1016/j.patrec.2006.12.018.
   Web of Science ®Google Scholar
• Abdelwahab M, El-hamid Fawzi A, HM E-B, MA E-D. 3D face identification: a survey. Int J Inf Sci Intell Syst. 2014;31(1):121–136.
   Google Scholar
• Urbanová P. Performance of distance-based matching algorithms in 3D facial identification. Egypt J Forensic Sci. 2016;6(2):135–151. doi:10.1016/j.ejfs.2016.04.004.
   Google Scholar
• Tangchaitrong K, Messer LB, Thomas CD, Townsend GC. Fourier analysis of facial profiles of young twins. American Journal of Physical Anthropology. 2000;113(3):369–379. doi:10.1002/1096-8644(200011)113:3<369::AID-AJPA7>3.0.CO;2-U.
   PubMed Web of Science ®Google Scholar
• Evison M, Dryden I, Fieller N, Mallett X, Morecroft L, Schofield D, Bruegge RV. Key parameters of face shape variation in 3D in a large sample. J Forensic Sci. 2010;55(1):159–162. doi:10.1111/j.1556-4029.2009.01213.x.
   PubMed Web of Science ®Google Scholar
• Cattaneo C, Cantatore A, Ciaffi R, Gibelli D, Cigada A, De Angelis D, Sala R. Personal identification by the comparison of facial profiles: testing the reliability of a high-resolution 3D-2D comparison model. J Forensic Sci. 2012;57(1):182–187. doi:10.1111/j.1556-4029.2011.01944.x.
   PubMed Web of Science ®Google Scholar
• Grother PJ, Ngan ML, Hanaoka KK, Recognition F. Vendor Test (FRVT) Part 2: identification; 2018 [cited 2020 Sep 6]. Available from: https://nfiles.nist.gov/w/dEmFbwW2
   Google Scholar
• Büttner M, Mommaerts MY. Photoshopping the face: simulated outcomes of orthofacial surgery. PMFA. 2015;2(2):1–5.
   Google Scholar
• Wermker K, Kleinheinz J, Jung S, Dirksen D. Soft tissue response and facial symmetry after orthognathic surgery. J Craniomaxillofac Surg. 2014;42(6):e339–345. doi:10.1016/j.jcms.2014.01.032.
   PubMed Web of Science ®Google Scholar
• Jandová M, Urbanová P. Sexual dimorphism in human facial expressions by 3D surface processing. HOMO - J Comp Hum Biol. 2018;69(3):98–109. doi:10.1016/j.jchb.2018.06.002.
   PubMed Web of Science ®Google Scholar
• Kortli Y, Jridi M, Falou AA, Atri M. Face recognition systems: a survey. Sens (Basel). 2020;20(2):342. doi:10.3390/s20020342.
   PubMed Web of Science ®Google Scholar
• Ngan ML, Grother PJ. Face Recognition Vendor Test (FRVT) - performance of automated age estimation algorithms; 2014 [cited 2020 May 3] Available from: https://www.nist.gov/publications/face-recognition-vendor-test-frvt-performance-automated-age-estimation-algorithms
   Google Scholar
• Ngan ML, Grother PJ, Hanaoka KK, Kuo JM. Face Recognition Vendor Test (FRVT) Part 4: MORPH - performance of automated face morph detection; 2020 [cited 2020 May 6] Available from: https://www.nist.gov/publications/face-recognition-vendor-test-frvt-part-4-morph-performance-automated-face-morph
   Google Scholar
• Ngan ML, Grother PJ, Hanaoka KK. Ongoing Face Recognition Vendor Test (FRVT) Part 6A: face recognition accuracy with masks using pre- COVID-19 algorithms; 2020 [cited 2020 Sep 6] Available from: https://www.nist.gov/publications/ongoing-face-recognition-vendor-test-frvt-part-6a-face-recognition-accuracy-masks-using
   Google Scholar
• Grother PJ, Ngan ML, Hanaoka KK. Face recognition vendor test Part 3: demographic effects; 2019 [cited 2020 May 3] Available from: https://www.nist.gov/publications/face-recognition-vendor-test-part-3-demographic-effects
   Google Scholar
• Ngan M, Grother P. Face Recognition Vendor Test (FRVT) performance of automated gender classification algorithms; 2015 [cited 2020 Mar 3] Available from: https://nvlpubs.nist.gov/nistpubs/ir/2015/NIST.IR.8052.pdf
   Google Scholar
• Urbanová P, Chalás I. Performance of matching algorithms in non-standard expression-variant faces. Proceedings to American Academy of Forensic Sciences 2016, 68th Annual Scientic Meeting of the American Academy of Forensic Sciences.
   Google Scholar
• Klare BF, Burge MJ, Klontz JC, Vorder Bruegge RW, Jain AK. Face recognition performance: role of demographic information. IEEE Trans Inf Forensics Secur. 2012;7(6):1789–1801. doi:10.1109/TIFS.2012.2214212.
   Web of Science ®Google Scholar
• Hunter D, Tiddeman B, Perrett D. Facial ageing. In: Wilkinson C, Rynn C, editors. Craniofacial identification. Cambridge: Cambridge University Press; 2012. p. 57–67.
   Google Scholar
• Gibelli D, Mapelli A, Obertová Z, Poppa P, Gabriel P, Ratnayake M, Tutkuviene J, Sforza C, Ritz-Timme S, Cattaneo C. Age changes of facial measurements in European young adult males: implications for the identification of the living. HOMO - J Comp Hum Biol. 2012;63(6):451–458. doi:10.1016/j.jchb.2012.08.002.
   PubMed Web of Science ®Google Scholar
• Andrup M, Elenius J, Ramirez E, Sjöström M. Indications and frequency of orthognathic surgery in Sweden - a questionnaire survey. Int J Oral Dent Health. 2015;1–5. doi:10.23937/2469-5734/1510019
   Google Scholar
• Al-Hassani A, Ahmad K, El-Menyar A, Abutaka A, Mekkodathil A, Peralta R, Al Khalil M, Al-Thani H. Prevalence and patterns of maxillofacial trauma: a retrospective descriptive study. Eur J Trauma Emerg Surg. 2019. Epub ahead of print. doi:10.1007/s00068-019-01174-6
   PubMedGoogle Scholar
• Donatsky O, Bjørn-Jørgensen J, Hermund NU, Nielsen H, Holmqvist-Larsen M, Nerder PH. Immediate postoperative outcome of orthognathic surgical planning, and prediction of positional changes in hard and soft tissue, independently of the extent and direction of the surgical corrections required. Br J Oral Maxillofac Surg, 495 2011:386–391 doi:10.1016/j.bjoms.2010.06.005.
   PubMed Web of Science ®Google Scholar
• Naran S, Steinbacher DM, Taylor JA. Current concepts in orthognathic surgery. Plast Reconstr Surg. 2018 Jun;141(6):925e–936e. doi:10.1097/PRS.0000000000004438
   PubMed Web of Science ®Google Scholar
• Baik HS, Kim SY. Facial soft-tissue changes in skeletal Class III orthognathic surgery patients analyzed with 3-dimensional laser scanning. Am J Orthod Dentofacial Orthop. 2010;138(2):167–178. doi:10.1016/j.ajodo.2010.02.022.
   PubMed Web of Science ®Google Scholar
• Cakirer B, Dean D, Palomo JM, Hans MG. Orthognathic surgery outcome analysis: 3-dimensional landmark geometric morphometrics. Int J Adult Orthodon Orthognath Surg. 2002;17(2):116–132.
   PubMedGoogle Scholar
• Terajima M, Yanagita N, Ozeki K, Hoshino Y, Mori N, Goto TK, Tokumori K, Aoki Y, Nakasimae A. Three-dimensional analysis system for orthognathic surgery patients with jaw deformities. Am Assoc Orthodontists. 2008;134(1):100–111.
   Google Scholar
• Urbanová P, Ferková Z, Jandová M, Jurda M, Černý D, Sochor J. Introducing the FIDENTIS 3D face database. Anthropol Rev. 2018;81(2):202–223. doi:10.2478/anre-2018-0016.
   Google Scholar
• Posnick JC. Definition and prevalence of dentofacial deformities. In: Posnick JC, editor. Principles and practice of orthognathic surgery; 2014. p. 61–68.
   Google Scholar
• Fetter V. Antropologie. Academia. 1967.
   Google Scholar