{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T06:43:13Z","timestamp":1764225793988,"version":"3.37.3"},"reference-count":18,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T00:00:00Z","timestamp":1654819200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T00:00:00Z","timestamp":1654819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Hochschule Mittweida, University of Applied Sciences"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["K\u00fcnstl Intell"],"published-print":{"date-parts":[[2022,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>During the prosecution process the primary objective is to prove criminal offences to the correct perpetrator to convict them with legal effect. However, in reality this may often be difficult to achieve. Suppose a suspect has been identified and is accused of a bank robbery. Due to the location of the crime, it can be assumed that there is sufficient image and video surveillance footage available, having recorded the perpetrator at the crime scene. Depending on the surveillance system used, there could be even high-resolution material available. In short, optimal conditions seem to be in place for further investigations, especially as far as the identification of the perpetrator and the collection of evidence of their participation in the crime are concerned. However, perpetrators usually act using some kind of concealment to hide their identity. In most cases, they disguise their faces and even their gait. Conventional investigation approaches and methods such as facial recognition and gait analysis then quickly reach their limits. For this reason, an approach based on anthropometric person-specific digital skeletons, so-called rigs, that is being researched by the COMBI research project is presented in this publication. Using these rigs, it should be possible to assign known identities, comparable to suspects, to unknown identities, comparable to perpetrators. The aim of the COMBI research project is to study the anthropometric pattern as a biometric identifier as well as to make it feasible for the standardised application in the taking of evidence by the police and prosecution. The approach is intended to present computer-aided opportunities for the identification of perpetrators that can support already established procedures.<\/jats:p>","DOI":"10.1007\/s13218-022-00761-x","type":"journal-article","created":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T07:02:30Z","timestamp":1654844550000},"page":"171-180","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["COMBI: Artificial Intelligence for Computer-Based Forensic Analysis of Persons"],"prefix":"10.1007","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3225-3104","authenticated-orcid":false,"given":"Sven","family":"Becker","sequence":"first","affiliation":[]},{"given":"Marie","family":"Heuschkel","sequence":"additional","affiliation":[]},{"given":"Sabine","family":"Richter","sequence":"additional","affiliation":[]},{"given":"Dirk","family":"Labudde","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,6,10]]},"reference":[{"issue":"4","key":"761_CR1","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1109\/TBIOM.2020.3008862","volume":"2","author":"W An","year":"2020","unstructured":"An W, Yu S, Makihara Y, Wu X, Xu C, Yu Y, Liao R, Yagi Y (2020) Performance evaluation of model-based gait on multi-view very large population database with pose sequences. IEEE Trans Biom Behav Identity Sci 2(4):421\u2013430","journal-title":"IEEE Trans Biom Behav Identity Sci"},{"key":"761_CR2","doi-asserted-by":"publisher","unstructured":"Andriluka M, Pishchulin L, Gehler P, Schiele B (2014) 2D human pose estimation: new benchmark and state of the art analysis. In: IEEE conference on computer vision and pattern recognition. San Diego, CA, USA, pp 3686\u20133693. https:\/\/doi.org\/10.1109\/CVPR.2014.471","DOI":"10.1109\/CVPR.2014.471"},{"key":"761_CR3","first-page":"1","volume":"11","author":"S Becker","year":"2018","unstructured":"Becker S, Spranger M, Heinke F, Grunert S, Labudde D (2018) A comprehensive framework for high resolution image-based 3d modeling and documentation of crime scenes and disaster sites. Int J Adv Syst Meas 11:1\u201312","journal-title":"Int J Adv Syst Meas"},{"key":"761_CR4","volume-title":"Blender 3D","author":"A Brito","year":"2007","unstructured":"Brito A (2007) Blender 3D. Novatec, New York"},{"issue":"1","key":"761_CR5","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","volume":"43","author":"Z Cao","year":"2021","unstructured":"Cao Z, Hidalgo G, Simon T, Wei SE, Sheikh Y (2021) OpenPose: realtime multi-person 2D pose estimation using part affinity fields. IEEE Trans Pattern Anal Mach Intell 43(1):172\u2013186. https:\/\/doi.org\/10.1109\/TPAMI.2019.2929257","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"761_CR6","doi-asserted-by":"publisher","unstructured":"Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE computer society conference on cmputer vision and pattern recognition (CVPR'05), vol 1. San Diego, CA, USA, pp 886\u2013893. https:\/\/doi.org\/10.1109\/CVPR.2005.177","DOI":"10.1109\/CVPR.2005.177"},{"issue":"4","key":"761_CR7","first-page":"6","volume":"6","author":"NV Flor","year":"2011","unstructured":"Flor NV (2011) Technology corner: virtual crime scene reconstruction: the basics of 3d modeling. J Digit Forensics Secur Law 6(4):6","journal-title":"J Digit Forensics Secur Law"},{"issue":"4","key":"761_CR8","doi-asserted-by":"publisher","first-page":"2518","DOI":"10.1007\/s10489-020-01918-7","volume":"51","author":"D Groos","year":"2021","unstructured":"Groos D, Ramampiaro H, Ihlen EA (2021) Efficientpose: scalable single-person pose estimation. Appl Intell 51(4):2518\u20132533","journal-title":"Appl Intell"},{"key":"761_CR9","volume-title":"Angewandte Statistik-Methodensammlung mit R","author":"J Hedderich","year":"2018","unstructured":"Hedderich J, Sachs L (2018) Angewandte Statistik-Methodensammlung mit R. Springer, Berlin"},{"key":"761_CR10","doi-asserted-by":"publisher","unstructured":"Huang F, Zeng A, Liu M, Lai Q, Xu Q (2020) DeepFuse: an IMU-aware network for real-time 3D human pose estimation from multi-view image. In: IEEE winter conference on applications of computer vision (WACV). Snowmass Village, CO, USA, pp 418\u2013427. https:\/\/doi.org\/10.1109\/WACV45572.2020.9093526","DOI":"10.1109\/WACV45572.2020.9093526"},{"key":"761_CR11","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1007\/978-1-61779-588-6_10","volume-title":"Homology modeling","author":"I Kufareva","year":"2011","unstructured":"Kufareva I, Abagyan R (2011) Methods of protein structure comparison. In: Orry A, Abagyan R (eds) Homology modeling. Springer, pp 231\u2013257"},{"issue":"4","key":"761_CR12","doi-asserted-by":"publisher","first-page":"568","DOI":"10.3390\/electronics9040568","volume":"9","author":"Q Lei","year":"2020","unstructured":"Lei Q, Zhang HB, Du JX, Hsiao TC, Chen CC (2020) Learning effective skeletal representations on rgb video for fine-grained human action quality assessment. Electronics 9(4):568","journal-title":"Electronics"},{"key":"761_CR13","doi-asserted-by":"crossref","unstructured":"Lin TY, Maire M, Belongie S, Hays J, Perona P, Ramanan D, Doll\u00e1r P, Zitnick CL (2014) Microsoft coco: common objects in context. In: European conference on computer vision. Springer, pp 740\u2013755","DOI":"10.1007\/978-3-319-10602-1_48"},{"issue":"4","key":"761_CR14","doi-asserted-by":"publisher","first-page":"889","DOI":"10.1111\/1556-4029.13382","volume":"62","author":"A Marcin","year":"2017","unstructured":"Marcin A, Maciej S, Robert S, Adam W (2017) Hierarchical, three-dimensional measurement system for crime scene scanning. J Forensic Sci 62(4):889\u2013899","journal-title":"J Forensic Sci"},{"issue":"5","key":"761_CR15","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1016\/j.scijus.2020.07.006","volume":"60","author":"R Mayne","year":"2020","unstructured":"Mayne R, Green H (2020) Virtual reality for teaching and learning in crime scene investigation. Sci Justice 60(5):466\u2013472","journal-title":"Sci Justice"},{"issue":"6","key":"761_CR16","first-page":"697","volume":"50","author":"D Raneri","year":"2018","unstructured":"Raneri D (2018) Enhancing forensic investigation through the use of modern three-dimensional (3d) imaging technologies for crime scene reconstruction. Aust J Forensic Sci 50(6):697\u2013707","journal-title":"Aust J Forensic Sci"},{"key":"761_CR17","doi-asserted-by":"crossref","unstructured":"Thakkar N, Farid H (2021) On the feasibility of 3d model-based forensic height and weight estimation. In: IEEE\/CVF conference on computer vision and pattern recognition (CVPR). Workshops, Nashville, TN, USA, pp 953\u2013961","DOI":"10.1109\/CVPRW53098.2021.00106"},{"key":"761_CR18","doi-asserted-by":"crossref","unstructured":"Tome D, Russell C, Agapito L (2017) Lifting from the deep: convolutional 3d pose estimation from a single image. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp 2500\u20132509","DOI":"10.1109\/CVPR.2017.603"}],"container-title":["KI - K\u00fcnstliche Intelligenz"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13218-022-00761-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13218-022-00761-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13218-022-00761-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T08:30:21Z","timestamp":1670833821000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13218-022-00761-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,10]]},"references-count":18,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,9]]}},"alternative-id":["761"],"URL":"https:\/\/doi.org\/10.1007\/s13218-022-00761-x","relation":{},"ISSN":["0933-1875","1610-1987"],"issn-type":[{"type":"print","value":"0933-1875"},{"type":"electronic","value":"1610-1987"}],"subject":[],"published":{"date-parts":[[2022,6,10]]},"assertion":[{"value":"24 September 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 April 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 June 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}