[{"abstract":[{"lang":"eng","text":"In this study, we examined the possibility of detecting different types of materials that contaminate carcasses during industrial pig slaughter using video image analysis and artificial intelligence (AI). A camera system was installed between evisceration and postmortem meat inspection on an industrial pig slaughter line with a capacity of 12,000 pigs per day. The pigs were photographed using five 2D cameras, and the images were analysed for contamination using an AI-based algorithm. The setup, which was developed and installed by CLK GmbH, performed under industrial conditions. In order to train the system, specifications were created for the most frequently occurring types of contamination, namely, intestinal contents, bile, stomach contents, and tubular rail fat. Afterward, the system was trained using annotated images. In principle, the system was able to recognize all types of contamination on the camera images; even pinhead-sized contaminations were visible. The agreement between the algorithm and the results of an expert assessor who assessed the images online agreed in 60% of the judgements. The agreement between experts using onsite assessment and those using online assessment by images was 73%. Thus, the kappa measure of agreement was κ = 0.1215 (p = 0.0199). Significantly higher recognition rates appear to be possible by adjusting the algorithm and increasing the number of training images. Thus, the system is a useful tool to preselect contaminated carcasses and to support postmortem inspection."}],"language":[{"iso":"eng"}],"doi":"10.3389/frfst.2026.1698416","title":"Detection of carcass contamination using video image analysis during industrial pig slaughter","author":[{"first_name":"Janna","last_name":"Tholen","id":"80924","full_name":"Tholen, Janna"},{"last_name":"Kirse","first_name":"Alina","full_name":"Kirse, Alina"},{"first_name":"Alexander","last_name":"Voß","full_name":"Voß, Alexander"},{"first_name":"Gereon","last_name":"Schulze Althoff","full_name":"Schulze Althoff, Gereon"},{"full_name":"Strotkötter, Lea","last_name":"Strotkötter","first_name":"Lea"},{"full_name":"Kreienbrock, Lothar","first_name":"Lothar","last_name":"Kreienbrock"},{"first_name":"Matthias","last_name":"Upmann","id":"12666","full_name":"Upmann, Matthias"}],"place":"Lausanne","publication_identifier":{"issn":["2674-1121"]},"intvolume":"         6","user_id":"83781","department":[{"_id":"DEP4028"},{"_id":"DEP4029"}],"date_updated":"2026-05-04T09:41:58Z","citation":{"chicago-de":"Tholen, Janna, Alina Kirse, Alexander Voß, Gereon Schulze Althoff, Lea Strotkötter, Lothar Kreienbrock und Matthias Upmann. 2026. Detection of carcass contamination using video image analysis during industrial pig slaughter. <i>Frontiers in Food Science and Technology</i> 6. doi:<a href=\"https://doi.org/10.3389/frfst.2026.1698416\">10.3389/frfst.2026.1698416</a>, .","mla":"Tholen, Janna, et al. “Detection of Carcass Contamination Using Video Image Analysis during Industrial Pig Slaughter.” <i>Frontiers in Food Science and Technology</i>, vol. 6, 1698416, 2026, <a href=\"https://doi.org/10.3389/frfst.2026.1698416\">https://doi.org/10.3389/frfst.2026.1698416</a>.","apa":"Tholen, J., Kirse, A., Voß, A., Schulze Althoff, G., Strotkötter, L., Kreienbrock, L., &#38; Upmann, M. (2026). Detection of carcass contamination using video image analysis during industrial pig slaughter. <i>Frontiers in Food Science and Technology</i>, <i>6</i>, Article 1698416. <a href=\"https://doi.org/10.3389/frfst.2026.1698416\">https://doi.org/10.3389/frfst.2026.1698416</a>","din1505-2-1":"<span style=\"font-variant:small-caps;\">Tholen, Janna</span> ; <span style=\"font-variant:small-caps;\">Kirse, Alina</span> ; <span style=\"font-variant:small-caps;\">Voß, Alexander</span> ; <span style=\"font-variant:small-caps;\">Schulze Althoff, Gereon</span> ; <span style=\"font-variant:small-caps;\">Strotkötter, Lea</span> ; <span style=\"font-variant:small-caps;\">Kreienbrock, Lothar</span> ; <span style=\"font-variant:small-caps;\">Upmann, Matthias</span>: Detection of carcass contamination using video image analysis during industrial pig slaughter. In: <i>Frontiers in Food Science and Technology</i> Bd. 6. Lausanne, Frontiers Media SA (2026)","ufg":"<b>Tholen, Janna u. a.</b>: Detection of carcass contamination using video image analysis during industrial pig slaughter, in: <i>Frontiers in Food Science and Technology</i> 6 (2026).","bjps":"<b>Tholen J <i>et al.</i></b> (2026) Detection of Carcass Contamination Using Video Image Analysis during Industrial Pig Slaughter. <i>Frontiers in Food Science and Technology</i> <b>6</b>.","chicago":"Tholen, Janna, Alina Kirse, Alexander Voß, Gereon Schulze Althoff, Lea Strotkötter, Lothar Kreienbrock, and Matthias Upmann. “Detection of Carcass Contamination Using Video Image Analysis during Industrial Pig Slaughter.” <i>Frontiers in Food Science and Technology</i> 6 (2026). <a href=\"https://doi.org/10.3389/frfst.2026.1698416\">https://doi.org/10.3389/frfst.2026.1698416</a>.","short":"J. Tholen, A. Kirse, A. Voß, G. Schulze Althoff, L. Strotkötter, L. Kreienbrock, M. Upmann, Frontiers in Food Science and Technology 6 (2026).","havard":"J. Tholen, A. Kirse, A. Voß, G. Schulze Althoff, L. Strotkötter, L. Kreienbrock, M. Upmann, Detection of carcass contamination using video image analysis during industrial pig slaughter, Frontiers in Food Science and Technology. 6 (2026).","ama":"Tholen J, Kirse A, Voß A, et al. Detection of carcass contamination using video image analysis during industrial pig slaughter. <i>Frontiers in Food Science and Technology</i>. 2026;6. doi:<a href=\"https://doi.org/10.3389/frfst.2026.1698416\">10.3389/frfst.2026.1698416</a>","ieee":"J. Tholen <i>et al.</i>, “Detection of carcass contamination using video image analysis during industrial pig slaughter,” <i>Frontiers in Food Science and Technology</i>, vol. 6, Art. no. 1698416, 2026, doi: <a href=\"https://doi.org/10.3389/frfst.2026.1698416\">10.3389/frfst.2026.1698416</a>.","van":"Tholen J, Kirse A, Voß A, Schulze Althoff G, Strotkötter L, Kreienbrock L, et al. Detection of carcass contamination using video image analysis during industrial pig slaughter. Frontiers in Food Science and Technology. 2026;6."},"publication":"Frontiers in Food Science and Technology","article_number":"1698416","date_created":"2026-04-30T13:02:33Z","type":"scientific_journal_article","year":"2026","volume":6,"publisher":"Frontiers Media SA","status":"public","_id":"13721","keyword":["artificial intelligence (AI)","bile contamination","contamination detection","faecal contamination","slaughter hygiene","tubular rail fat"],"publication_status":"published"},{"abstract":[{"lang":"eng","text":"Deploying digital twins across the broader building stock is constrained by a key bottleneck: high-quality 3D content from LiDAR or photogrammetry remains labor-intensive and difficult to scale. We introduce Generative Twins (GT), a workflow that shifts digital twin creation from explicit geometric reconstruction toward probabilistic 3D synthesis. The pipeline takes a\r\nsingle street-level façade photograph, corrects perspective distortion and removes occlusions, uses an instruction-conditioned multimodal image model to synthesise an isometric view of the building, and passes that view to an image-to-3D reconstruction model that leverages learned shape priors to produce a textured mesh without manual modelling. Three image to-3D platforms (Hitem3D, Hyper3D and Hunyuan3D 3.1) are compared on identical isometric inputs and assessed on architectural boundary clarity. We demonstrate GT through two applied cases: (i) reconstruction of ordinary residential streets in Detmold as stimuli for a virtual-reality study of multi sensory urban perception, and (ii) Green Editor, a design-exploration tool in which façade greenery is added or removed at the image layer before mesh generation.\r\nTogether these cases position Generative Twins as a scalable pathway for the digitization of ordinary building stock, with emphasis on controllability, editability, and iterative design workflows."}],"language":[{"iso":"eng"}],"doi":"10.52842/conf.ecaade.2026.1.619","title":"Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis","publication_identifier":{"issn":["2684-1843"]},"author":[{"first_name":"Mohamed Khaled","last_name":"Ashmawy","full_name":"Ashmawy, Mohamed Khaled","id":"81286"},{"full_name":"Akay, Buse","id":"88405","last_name":"Akay","first_name":"Buse"},{"id":"74171","full_name":"Balderrama, Alvaro","last_name":"Balderrama","first_name":"Alvaro","orcid":"0000-0002-4118-2838"}],"intvolume":"         1","user_id":"83781","department":[{"_id":"DEP1634"}],"publication":"eCAADe proceedings","citation":{"bjps":"<b>Ashmawy MK, Akay B and Balderrama A</b> (2026) <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. eCAADe.","ufg":"<b>Ashmawy, Mohamed Khaled/Akay, Buse/Balderrama, Alvaro</b>: Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis, Bd. 1, o. O. 2026.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Ashmawy, Mohamed Khaled</span> ; <span style=\"font-variant:small-caps;\">Akay, Buse</span> ; <span style=\"font-variant:small-caps;\">Balderrama, Alvaro</span>: <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. Bd. 1 : eCAADe, 2026","van":"Ashmawy MK, Akay B, Balderrama A. Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis. Vol. 1, eCAADe proceedings. eCAADe; 2026.","ieee":"M. K. Ashmawy, B. Akay, and A. Balderrama, <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>, vol. 1. eCAADe, 2026. doi: <a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">10.52842/conf.ecaade.2026.1.619</a>.","apa":"Ashmawy, M. K., Akay, B., &#38; Balderrama, A. (2026). Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis. In <i>eCAADe proceedings</i> (Vol. 1). eCAADe. <a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">https://doi.org/10.52842/conf.ecaade.2026.1.619</a>","mla":"Ashmawy, Mohamed Khaled, et al. “Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis.” <i>ECAADe Proceedings</i>, vol. 1, eCAADe, 2026, <a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">https://doi.org/10.52842/conf.ecaade.2026.1.619</a>.","chicago-de":"Ashmawy, Mohamed Khaled, Buse Akay und Alvaro Balderrama. 2026. <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. <i>eCAADe proceedings</i>. Bd. 1. eCAADe. doi:<a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">10.52842/conf.ecaade.2026.1.619</a>, .","havard":"M.K. Ashmawy, B. Akay, A. Balderrama, Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis, eCAADe, 2026.","short":"M.K. Ashmawy, B. Akay, A. Balderrama, Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis, eCAADe, 2026.","chicago":"Ashmawy, Mohamed Khaled, Buse Akay, and Alvaro Balderrama. <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. <i>ECAADe Proceedings</i>. Vol. 1. eCAADe, 2026. <a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">https://doi.org/10.52842/conf.ecaade.2026.1.619</a>.","ama":"Ashmawy MK, Akay B, Balderrama A. <i>Towards Generative Twins: An AI Based Pipeline from Explicit 3D Reconstruction to Probabilistic Synthesis</i>. Vol 1. eCAADe; 2026. doi:<a href=\"https://doi.org/10.52842/conf.ecaade.2026.1.619\">10.52842/conf.ecaade.2026.1.619</a>"},"date_updated":"2026-10-01T14:28:23Z","year":"2026","type":"conference_editor_article","date_created":"2026-09-30T10:14:15Z","status":"public","volume":1,"publisher":"eCAADe","conference":{"end_date":"2026-09-11","start_date":"2026-09-07","location":"Lübeck","name":"44. eCAADe-Konferenz"},"keyword":["Digital Twins","Virtual Reality (VR","Artificial Intelligence (AI)","Image-to-3D","Generative Design."],"publication_status":"published","_id":"14070"}]