2024W

• Bachelor Thesis / 183.582 / PR
• Introduction to Programming 1 / 185.A91 / VU

2025S

• Bachelor Thesis / 183.582 / PR
• Introduction to Programming 1 / 185.A91 / VU
• Introduction to Programming 2 / 185.A92 / VU

• Industrie-Masterarbeit Manuel Waibel
  2024 – 2025 / Hexagon Technology Center GmbH
• Domain-adaptive Remote sensing Image Analysis with Human-in-the-loop
  2020 – 2024 / Austrian Research Promotion Agency (FFG)
  Publications: 136164 / 153454 / 148085 / 187702 / 188929 / 192267 / 192272 / 190137 / 193453 / 190618 / 190292 / 190245 / 192769 / 199344 / 199738 / 203805 / 203929 / 208705 / 208533 / 135846
• Mite Invasion Control Camera (MIC-Cam)
  2016 – 2018 / Vienna Business Agency (WAW)
• Infos@ourHouse - Interaktive Infodisplays für Hausgemeinschaften
  2014 – 2016 / Vienna Business Agency (WAW)
• Image-based cLassification of Ancient Coins
  2010 – 2014 / Austrian Science Fund (FWF)
• On the spot event detection with low cost camera modules and communication trough robust networks from building automation
  2010 – 2012 / Austrian Research Promotion Agency (FFG)
• Smart Homes for Elderly People
  2009 – 2012 / Austrian Research Promotion Agency (FFG)
• Behaviour analysis for banks based on image analysis
  2008 – 2011 / Austrian Research Promotion Agency (FFG)
• Preventing Illicit Coin Trade through Unsupervised Retrieval E-services
  2007 – 2009 / European Commission
  Publication: 27745

2024

• Machine learning and computer vision techniques in continuous beehive monitoring applications: A survey / Bilik, S., Zemcik, T., Kratochvila, L., Ricanek, D., Richter, M., Zambanini, S., & Horak, K. (2024). Machine learning and computer vision techniques in continuous beehive monitoring applications: A survey. Computers and Electronics in Agriculture, 217, Article 108560. https://doi.org/10.1016/j.compag.2023.108560
• Making Archives Searchable: Vision-Language Models for Classification of Historical Aerial Imagery / Burges, M., Zambanini, S., & Sablatnig, R. (2024). Making Archives Searchable: Vision-Language Models for Classification of Historical Aerial Imagery. In GeoSearch ’24: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data (pp. 1–8). https://doi.org/10.1145/3681769.3698578
  Project: DoRIAH (2020–2024)
• CHAI: Craters in Historical Aerial Images / Burges, M., Zambanini, S., & Pirker, P. (2024). CHAI: Craters in Historical Aerial Images. In 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (pp. 8241–8250). https://doi.org/10.1109/WACV57701.2024.00807
  Project: DoRIAH (2020–2024)

2023

• Exploring Learning-Based Approaches for Bomb Crater Detection in Historical Aerial Images / Burges, M., Zambanini, S., & Sablatnig, R. (2023). Exploring Learning-Based Approaches for Bomb Crater Detection in Historical Aerial Images. In Proceedings of the OAGM Workshop 2022 (pp. 60–66). https://doi.org/10.3217/978-3-85125-954-4-09
  Project: DoRIAH (2020–2024)

2022

• Color-Light Multi Cascade Network for Single Image Depth Prediction on One Perspective Artifact Images / Frisky, A. Z. K., Brenner, S., Zambanini, S., & Sablatnig, R. (2022). Color-Light Multi Cascade Network for Single Image Depth Prediction on One Perspective Artifact Images. In G. F. Farinella, P. Radeva, & K. Bouatouch (Eds.), Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (pp. 909–916). https://doi.org/10.5220/0010801100003124

2021

• MCCNet: Multi-Color Cascade Network with Weight Transfer for Single Image Depth Prediction on Outdoor Relief Images / Frisky, A. Z. K., Putranto, A., Zambanini, S., & Sablatnig, R. (2021). MCCNet: Multi-Color Cascade Network with Weight Transfer for Single Image Depth Prediction on Outdoor Relief Images. In Pattern Recognition. ICPR International Workshops and Challenges (pp. 263–278). https://doi.org/10.1007/978-3-030-68787-8_19
• Investigation of Single Image Depth Prediction Under Different Lighting Conditions: A Case Study of Ancient Roman Coins / Frisky, A. Z. K., Harjoko, A., Awaludin, L., Zambanini, S., & Sablatnig, R. (2021). Investigation of Single Image Depth Prediction Under Different Lighting Conditions: A Case Study of Ancient Roman Coins. Journal on Computing and Cultural Heritage, 14(4), 1–17. https://doi.org/10.1145/3465742
• Registered Relief Depth (RRD) borobudur dataset for single-frame depth prediction on one-side artifacts / Frisky, A. Z. K., Harjoko, A., Awaludin, L., Dharmawan, A., Augoestien, N. G., Candradewi, I., Hujja, R. M., Putranto, A., Hartono, T., Suhartono, Y., Zambanini, S., & Sablatnig, R. (2021). Registered Relief Depth (RRD) borobudur dataset for single-frame depth prediction on one-side artifacts. Data in Brief, 35(106853), 106853. https://doi.org/10.1016/j.dib.2021.106853
• Deep ancient Roman Republican coin classification via feature fusion and attention / Anwar, H., Anwar, S., Zambanini, S., & Porikli, F. (2021). Deep ancient Roman Republican coin classification via feature fusion and attention. Pattern Recognition, 114(107871), 107871. https://doi.org/10.1016/j.patcog.2021.107871

2020

• Detection of Parking Cars in Stereo Satellite Images / Zambanini, S., Loghin, A.-M., Pfeifer, N., Soley, E. M., & Sablatnig, R. (2020). Detection of Parking Cars in Stereo Satellite Images. Remote Sensing, 12(13), 2170. https://doi.org/10.3390/rs12132170

2019

• Feature-based groupwise registration of historical aerial images to present-day ortho-photo maps / Zambanini, S. (2019). Feature-based groupwise registration of historical aerial images to present-day ortho-photo maps. Pattern Recognition, 90, 66–77. https://doi.org/10.1016/j.patcog.2019.01.024

2018

• An Investigation of Optimal Light Source Setups for Photometric Stereo Reconstruction of Historical Coins / Brenner, S., Zambanini, S., & Sablatnig, R. (2018). An Investigation of Optimal Light Source Setups for Photometric Stereo Reconstruction of Historical Coins. In S. Brenner, S. Zambanini, & R. Sablatnig (Eds.), GCH 2018 Eurographics Workshop on Graphics and Cultural Heritage (pp. 203–206). Eurographics. https://doi.org/10.2312/gch.20181362
• Detection of Bomb Craters in WWII Aerial Images / Brenner, S., Zambanini, S., & Sablatnig, R. (2018). Detection of Bomb Craters in WWII Aerial Images. In M. Welk, M. Urschler, & P. M. Roth (Eds.), Proceedings of the OAGM Workshop 2018 Medical Image Analysis (pp. 94–97). Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-603-1-20

2017

• Adapting to the Problem at Hand: Image Registration and Object Detection for Automatic WW2 Aerial Photograph Processing / Zambanini, S., & Sablatnig, R. (2017). Adapting to the Problem at Hand: Image Registration and Object Detection for Automatic WW2 Aerial Photograph Processing. 45th Computer Applications and Quantitative Methods in Archaeology Conference (CAA 2017), Atlanta, United States of America (the). http://hdl.handle.net/20.500.12708/86632
• A Hough Voting Strategy for Registering Historical Aerial Images to Present-Day Satellite Imagery / Zambanini, S., & Sablatnig, R. (2017). A Hough Voting Strategy for Registering Historical Aerial Images to Present-Day Satellite Imagery. In Image Analysis and Processing - ICIAP 2017 (pp. 595–605). Springer. https://doi.org/10.1007/978-3-319-68560-1_53
• Visual Analytics for Multitemporal Aerial Image Georeferencing / Amor-Amoros, A., Federico, P., Miksch, S., Zambanini, S., Brenner, S., & Sablatnig, R. (2017). Visual Analytics for Multitemporal Aerial Image Georeferencing. In M. Sedlmair & C. Tominski (Eds.), Proceedings of the EuroVis Workshop on Visual Analytics (EuroVA) (pp. 55–59). The Eurographics Association. https://doi.org/10.2312/eurova.20171120
• Image Registration and Object Detection for Assessing Unexploded Ordnance Risks ‐ A Status Report of the DeVisOR Project / Brenner, S., Zambanini, S., & Sablatnig, R. (2017). Image Registration and Object Detection for Assessing Unexploded Ordnance Risks ‐ A Status Report of the DeVisOR Project. In P. M. Roth, M. Vincze, W. Kubinger, A. Müller, B. Blaschitz, & S. Štolc (Eds.), Proceedings of the OAGM & ARW Joint Workshop Vision, Automation and Robotics (pp. 109–110). Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-524-9

2016

• Computer Vision applied to Historical Air Photos: The Registration and Object Detection Challenge / Zambanini, S., Hollaus, F., & Sablatnig, R. (2016). Computer Vision applied to Historical Air Photos: The Registration and Object Detection Challenge. 44th Computer Applications and Quantitative Methods in Archaeology Conference (CAA 2016), Oslo, Norway. http://hdl.handle.net/20.500.12708/86372
• Sensor Study for Monitoring Varroa Mites on Honey Bees (Apis mellifera) / Schurischuster, S., Zambanini, S., Kampel, M., & Lamp, B. (2016). Sensor Study for Monitoring Varroa Mites on Honey Bees (Apis mellifera). In Proc. of Visual observation and analysis of Vertebrate And Insect Behavior Workshop (VAIB 2016) (p. 4). http://hdl.handle.net/20.500.12708/56648
• DeVisOR - Detection and Visualization of Unexploded Ordnance Risks / Zambanini, S., Hollaus, F., & Sablatnig, R. (2016). DeVisOR - Detection and Visualization of Unexploded Ordnance Risks. In Vision Meets Robotics, Proceedings of the ÖAGM Workshop 2016 (pp. 1–2). http://hdl.handle.net/20.500.12708/56647

2015

• Shape Analysis and Geometric Modelling / Kampel, M., & Zambanini, S. (2015). Shape Analysis and Geometric Modelling. In Mathematics and Archaeology (pp. 137–156). CRC Press. http://hdl.handle.net/20.500.12708/28778
• Invariant Image-Based Species Classification of Butterflies and Reef Fish / Anwar, H., Zambanini, S., & Kampel, M. (2015). Invariant Image-Based Species Classification of Butterflies and Reef Fish. In Machine Vision of Animals and their Behaviour (p. 8). http://hdl.handle.net/20.500.12708/56047
• Ancient Coin Classification Using Reverse Motif Recognition: Image-based classification of Roman Republican coins / Anwar, H., Zambanini, S., Kampel, M., & Vondrovec, K. (2015). Ancient Coin Classification Using Reverse Motif Recognition: Image-based classification of Roman Republican coins. IEEE Signal Processing Magazine, 32(4), 64–74. https://doi.org/10.1109/msp.2015.2409331
• Efficient Scale- and Rotation-Invariant Encoding of Visual Words for Image Classification / Anwar, H., Zambanini, S., & Kampel, M. (2015). Efficient Scale- and Rotation-Invariant Encoding of Visual Words for Image Classification. IEEE Signal Processing Letters, 22(10), 1762–1765. https://doi.org/10.1109/lsp.2015.2432851
• Coarse-grained ancient coin classification using image-based reverse side motif recognition / Anwar, H., Zambanini, S., & Kampel, M. (2015). Coarse-grained ancient coin classification using image-based reverse side motif recognition. Machine Vision and Applications, 26(2–3), 295–304. https://doi.org/10.1007/s00138-015-0665-2

2014

• Encoding Spatial Arrangements of Visual Words for Rotation-Invariant Image Classification / Anwar, H., Zambanini, S., & Kampel, M. (2014). Encoding Spatial Arrangements of Visual Words for Rotation-Invariant Image Classification. In Pattern Recognition 36th German Conference, GCPR 2014, Münster, Germany, September 2-5, 2014, Proceedings (pp. 443–452). Lecture Note in Computer Science. https://doi.org/10.1007/978-3-319-11752-2_36
• A Rotation-invariant Bag of Visual Words Model for Symbols-based Ancient Coin Classification / Anwar, H., Zambanini, S., & Kampel, M. (2014). A Rotation-invariant Bag of Visual Words Model for Symbols-based Ancient Coin Classification. In IEEE International Conference on Image Processing 2014 (pp. 5257–5261). IEEE. http://hdl.handle.net/20.500.12708/55262
• Insensitive image comparison in the absence of training data / Zambanini, S. (2014). Insensitive image comparison in the absence of training data [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2014.25346
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• A Large-Scale Evaluation of Correspondence-Based Coin Classification on Roman Republican Coinage / Zambanini, S., & Kampel, M. (2014). A Large-Scale Evaluation of Correspondence-Based Coin Classification on Roman Republican Coinage. In R. Klein & P. Santos (Eds.), GCH 2014 - Eurographics Workshop on Graphics and Cultural Heritage. Eurographics. https://doi.org/10.2312/gch.20141326
• Reading the legends of Roman Republican coins / Kavelar, A., Zambanini, S., & Kampel, M. (2014). Reading the legends of Roman Republican coins. Journal on Computing and Cultural Heritage, 7(1), 1–20. https://doi.org/10.1145/2583115
• Concluding ILAC - An Interdisciplinary Approach towards Image-Based Classification of Ancient Coins / Kavelar, A., Zambanini, S., & Kampel, M. (2014). Concluding ILAC - An Interdisciplinary Approach towards Image-Based Classification of Ancient Coins. 42nd Computer Applications and Quantitative Methods in Archaeology Conference (CAA 2014), Paris, Frankreich, EU. http://hdl.handle.net/20.500.12708/85902
• Multi-image morphing: Summarizing visual information from similar ancient coin image regions / Hödlmoser, S., Zambanini, S., & Kampel, M. (2014). Multi-image morphing: Summarizing visual information from similar ancient coin image regions. In 2014 International Conference on Virtual Systems & Multimedia (VSMM). 20th International Conference on Virtual Systems & Multimedia, Hong Kong, Non-EU. https://doi.org/10.1109/vsmm.2014.7136662
• Classifying Ancient Coins by Local Feature Matching and Pairwise Geometric Consistency Evaluation / Zambanini, S., Kavelar, A., & Kampel, M. (2014). Classifying Ancient Coins by Local Feature Matching and Pairwise Geometric Consistency Evaluation. In 2014 22nd International Conference on Pattern Recognition. 22nd International Conference on Pattern Recognition, Stockholm, Schweden, EU. IEEE. https://doi.org/10.1109/icpr.2014.523

2013

• Supporting Ancient Coin Classification by Image-Based Reverse Side Symbol Recognition / Anwar, H., Zambanini, S., & Kampel, M. (2013). Supporting Ancient Coin Classification by Image-Based Reverse Side Symbol Recognition. In Computer Analysis of Images and Patterns (pp. 17–25). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-40246-3_3
• A Bag of Visual Words Approach for Symbols-Based Coarse-Grained Ancient Coin Classification / Anwar, H., Zambanini, S., & Kampel, M. (2013). A Bag of Visual Words Approach for Symbols-Based Coarse-Grained Ancient Coin Classification. In Proceedings of the 37th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM/AAPR), 2013 (p. 8). arXiv.org. http://hdl.handle.net/20.500.12708/54915
• Improving Ancient Roman Coin Classification by Fusing Exemplar-Based Classification and Legend Recognition / Zambanini, S., Kavelar, A., & Kampel, M. (2013). Improving Ancient Roman Coin Classification by Fusing Exemplar-Based Classification and Legend Recognition. In New Trends in Image Analysis and Processing – ICIAP 2013 (pp. 149–158). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-41190-8_17
• Evaluation of Low-Level Image Representations for Illumination-Insensitive Recognition of Textureless Objects / Zambanini, S., & Sablatnig, R. (2013). Evaluation of Low-Level Image Representations for Illumination-Insensitive Recognition of Textureless Objects. In Image Analysis and Processing – ICIAP 2013 (pp. 71–80). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-41181-6_8
• A Local Image Descriptor Robust to Illumination Changes / Zambanini, S., & Kampel, M. (2013). A Local Image Descriptor Robust to Illumination Changes. In Image Analysis (pp. 11–21). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-38886-6_2
• THE ILAC-PROJECT: SUPPORTING ANCIENT COIN CLASSIFICATION BY MEANS OF IMAGE ANALYSIS / Kavelar, A., Zambanini, S., Kampel, M., Vondrovec, K., & Siegl, K. (2013). THE ILAC-PROJECT: SUPPORTING ANCIENT COIN CLASSIFICATION BY MEANS OF IMAGE ANALYSIS. In The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (pp. 373–378). ISPRS Archives. https://doi.org/10.5194/isprsarchives-xl-5-w2-373-2013
• Reading Ancient Coin Legends: Object Recognition vs. OCR / Kavelar, A., Zambanini, S., & Kampel, M. (2013). Reading Ancient Coin Legends: Object Recognition vs. OCR. In Proceedings of the 37th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM/AAPR), 2013 (p. 9). arXiv.org. http://hdl.handle.net/20.500.12708/54914

2012

• Coinage, Digitization, and the World-Wide Web: Numismatics and the COINS Project / Jarrett, J., Zambanini, S., Huber-Mörk, R., & Felicetti, A. (2012). Coinage, Digitization, and the World-Wide Web: Numismatics and the COINS Project. In B. Nelson & M. Terras (Eds.), Digitizing Medieval and Early Modern Material Culture (pp. 455–485). Iter, Inc., and the Arizona Center for Medieval and Renaissance Studies. http://hdl.handle.net/20.500.12708/27745
  Project: COINS (2007–2009)
• Automatic Coin Classification and Identification / Huber-Mörk, R., Nölle, M., Rubik, M., Hödlmoser, M., Zambanini, S., & Kampel, M. (2012). Automatic Coin Classification and Identification. In Advances in Object Recognition Systems. InTech. https://doi.org/10.5772/35795
• Evaluating Camera-based Methods for Mobile Markerless Fingertip Detection / Lasinger, K., Baldauf, M., & Zambanini, S. (2012). Evaluating Camera-based Methods for Mobile Markerless Fingertip Detection. In Proceedings of the 2nd International Workshop on Smart Mobile Applications (p. 6). http://hdl.handle.net/20.500.12708/54375
• Automatically Recognizing the Legends of Ancient Roman Republican Coins / Kavelar, A., Zambanini, S., & Kampel, M. (2012). Automatically Recognizing the Legends of Ancient Roman Republican Coins. Computer Applications and Quantitative Methods in Archaeology (CAA) 2012, Southampton, Großbritannien, EU. http://hdl.handle.net/20.500.12708/85449
• Computergestützte Bestimmung Antiker Münzen / Zambanini, S. (2012). Computergestützte Bestimmung Antiker Münzen. Forschung im Museum, Kunsthistorisches Museum, Wien, Austria. http://hdl.handle.net/20.500.12708/84905
• Word detection applied to images of ancient Roman coins / Kavelar, A., Zambanini, S., & Kampel, M. (2012). Word detection applied to images of ancient Roman coins. In 2012 18th International Conference on Virtual Systems and Multimedia. 18th International Conference on Virtual Systems and Multimedia (VSMM), 2012, Mailand, Italien, EU. IEEE. https://doi.org/10.1109/vsmm.2012.6365981
• Coarse-to-Fine Correspondence Search for Classifying Ancient Coins / Zambanini, S., & Kampel, M. (2012). Coarse-to-Fine Correspondence Search for Classifying Ancient Coins. In Computer Vision -- ACCV 2012 Workshops. 2nd ACCV Workshop on e-Heritage, Daejeon, Südkorea, Non-EU. http://hdl.handle.net/20.500.12708/54376
• Using Image Analysis to Match a Coin to a Database / Zambanini, S., & Kampel, M. (2012). Using Image Analysis to Match a Coin to a Database. In Archaeology in the Digital Era Papers from the 40th Annual Conference of Computer Applications and Quantitative Methods in Archaeology (pp. 195–199). Amsterdam University Press. http://hdl.handle.net/20.500.12708/54374

2011

• Identification of ancient coins based on fusion of shape and local features / Huber-Mörk, R., Zambanini, S., Zaharieva, M., & Kampel, M. (2011). Identification of ancient coins based on fusion of shape and local features. Machine Vision and Applications, 22(6), 983–994. https://doi.org/10.1007/s00138-010-0283-y
• Markerless visual fingertip detection for natural mobile device interaction / Baldauf, M., Zambanini, S., Fröhlich, P., & Reichl, P. (2011). Markerless visual fingertip detection for natural mobile device interaction. In Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services - MobileHCI ’11. 13th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI 2011), Stockholm, Schweden, EU. ACM. https://doi.org/10.1145/2037373.2037457
• Towards Markerless Visual Finger Detection for Gestural Interaction with Mobile Devices / Baldauf, M., Zambanini, S., Lasinger, K., & Reichl, P. (2011). Towards Markerless Visual Finger Detection for Gestural Interaction with Mobile Devices. Workshop on Smart Mobile Applications, San Francisco, USA, Non-EU. http://hdl.handle.net/20.500.12708/85179
• Audiovisual Assistance for the Elderly - An Overview of the FEARLESS Project / Planinc, R., Kampel, M., & Zambanini, S. (2011). Audiovisual Assistance for the Elderly - An Overview of the FEARLESS Project. In Toward Useful Services for Elderly and People with Disabilities (pp. 225–229). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-21535-3_31
• Automatic Coin Classification by Image Matching / Zambanini, S., & Kampel, M. (2011). Automatic Coin Classification by Image Matching. In F. Niccolucci, M. Dellepiane, S. Pena Serna, H. Rushmeier, & L. Van Gool (Eds.), VAST11: The 12th International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage (pp. 65–72). Eurographics Association. https://doi.org/10.2312/VAST/VAST11/065-072
• An Automatic Image Based Coin Classification System for Numismatic Databases / Zambanini, S., & Kampel, M. (2011). An Automatic Image Based Coin Classification System for Numismatic Databases. CHNT 2011 16th International Conference on Cultural Heritage and New Technologies, Wien, Österreich, Austria. http://hdl.handle.net/20.500.12708/85299

2010

• 3D acquisition of historical coins and its application area in numismatics / Zambanini, S., Schlapke, M., Hödlmoser, M., & Kampel, M. (2010). 3D acquisition of historical coins and its application area in numismatics. In D. Stork, J. Coddington, & A. Bentkowska-Kafel (Eds.), Computer Vision and Image Analysis of Art. SPIE & IS&T-The Society for Imaging Science and Technology. http://hdl.handle.net/20.500.12708/53358
• Automatic image-based assessment of lesion development during hemangioma follow-up examinations / Zambanini, S., Sablatnig, R., Maier, H., & Langs, G. (2010). Automatic image-based assessment of lesion development during hemangioma follow-up examinations. Artificial Intelligence in Medicine, 50(2), 83–94. https://doi.org/10.1016/j.artmed.2010.06.003
• Detecting Falls at Homes Using a Network of Low-Resolution Cameras / Zambanini, S., Machajdik, J., & Kampel, M. (2010). Detecting Falls at Homes Using a Network of Low-Resolution Cameras. In 10th IEEE International Conference on Information Technology and Applications in Biomedicine (p. 4). IEEE. http://hdl.handle.net/20.500.12708/53377
• Computer Vision for an Independent Lifestyle of the Elderly - An Overview of the MuBisA Project / Zambanini, S., Kampel, M., & Machajdik, J. (2010). Computer Vision for an Independent Lifestyle of the Elderly - An Overview of the MuBisA Project. AALIANCE Conference, Malaga, Spanien, EU. http://hdl.handle.net/20.500.12708/85023
• Introducing a Statistical Behavior Model into Camera-Based Fall Detection / Zweng, A., Zambanini, S., & Kampel, M. (2010). Introducing a Statistical Behavior Model into Camera-Based Fall Detection. In G. Bebis, R. Boyle, B. Parvin, D. Koracin, R. Chung, R. Hammound, M. Hussain, T. Kar-Han, R. Crawfis, D. Thalmann, D. Kao, & L. Avila (Eds.), Advances in Visual Computing (pp. 163–172). Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/53486
• FeEval A Dataset for Evaluation of Spatio-temporal Local Features / Stöttinger, J., Zambanini, S., Khan, R., & Hanbury, A. (2010). FeEval A Dataset for Evaluation of Spatio-temporal Local Features. In M. Cetin, K. Boyer, & S.-W. Lee (Eds.), 2010 20th International Conference on Pattern Recognition. IEEE. https://doi.org/10.1109/icpr.2010.128
• Evaluation of Historical 3D Coin Models / Hödlmoser, M., Zambanini, S., Schlapke, M., & Kampel, M. (2010). Evaluation of Historical 3D Coin Models. In Proceedings of the 38th Annual Conference on Computer Applications and Quantitative Methods in Archaeology, Granada, Spain, April 2010 (pp. 499–504). Archaeopress. http://hdl.handle.net/20.500.12708/53465
• Fusion of Data from Multiple Cameras for Fall Detection / Machajdik, J., Zambanini, S., & Kampel, M. (2010). Fusion of Data from Multiple Cameras for Fall Detection. In B. Gottfried & H. Aghajan (Eds.), Proceedings of the 5th Workshop on Behaviour Monitoring and Interpretation, BMI’10, Karlsruhe, Germany, September 21, 2010 (p. 7). CEUR-WS.org. http://hdl.handle.net/20.500.12708/53369
• Early versus Late Fusion in a Multiple Camera Network for Fall Detection / Zambanini, S., Machajdik, J., & Kampel, M. (2010). Early versus Late Fusion in a Multiple Camera Network for Fall Detection. In P. Blauensteiner, M. Lettner, & J. Stöttinger (Eds.), Computer Vision in a Global Society - 34th Annual Workshop of the Austrian Association for Pattern Recognition (AAPR) and the WG Visual Computing of the Austrian Computer Society (pp. 15–22). Österreichische Computer Gesellschaft. http://hdl.handle.net/20.500.12708/53364

2009

• Robust Automatic Segmentation of Ancient Coins / Zambanini, S., & Kampel, M. (2009). Robust Automatic Segmentation of Ancient Coins. In 4th International Conference on Computer Vision Theory and Applications (pp. 273–276). http://hdl.handle.net/20.500.12708/52902
• Automated Multi-Camera Surveillance for the Prevention and Investigation of Bank Robberies in Austria: A Case Study / Zambanini, S., Blauensteiner, P., & Kampel, M. (2009). Automated Multi-Camera Surveillance for the Prevention and Investigation of Bank Robberies in Austria: A Case Study. In Proceedings. 3rd international Conference on Imaging for Crime Detection and Prevention, London, EU. http://hdl.handle.net/20.500.12708/52908
• Image Based Measurement of Ancient Coins / Herrmann, M., Kampel, M., & Zambanini, S. (2009). Image Based Measurement of Ancient Coins. In Proceedings of the 37th Annual Conference on Computer Applications and Quantitative Methods in Archaeology (CAA’09). 37th Annual Conference on Computer Applications and Quantitative Methods in Archaeology (CAA’09), Williamsburg, Virginia, USA, Non-EU. http://hdl.handle.net/20.500.12708/52907
• Acquisition of 3D Coin Models and Their Potential in Numismatic Research / Zambanini, S., Schlapke, M., Müller, A., & Kampel, M. (2009). Acquisition of 3D Coin Models and Their Potential in Numismatic Research. In Konferenzband EVA 2009 Berlin. EVA Berlin 2009, Berlin, EU. http://hdl.handle.net/20.500.12708/52906
• An Automatic Method to Determine the Diameter of Historical Coins in Images / Zambanini, S., Herrmann, M., & Kampel, M. (2009). An Automatic Method to Determine the Diameter of Historical Coins in Images. In Scientific Computing for Cultural Heritage SCCH 2009. Scientific Computing for Cultural Heritage, SCCH2009, Heidelberg, EU. http://hdl.handle.net/20.500.12708/52905
• Historical Coins in 3D: Aquisition and Numismatic Applications / Zambanini, S., Schlapke, M., & Kampel, M. (2009). Historical Coins in 3D: Aquisition and Numismatic Applications. In 10th International Symposium on Virtual Reality, Archaeology and Cultural Heritage - VAST-STAR, Short and Project Proceedings (pp. 49–52). http://hdl.handle.net/20.500.12708/52903

2008

• Image-Based Classification Of Ancient Coins / Kampel, M., Vondrovec, K., Zaharieva, M., & Zambanini, S. (2008). Image-Based Classification Of Ancient Coins. In Proceedings of the 14th International Conference on Virtual Systems and Multimedia. VSMM09, Limassol, Cyprus, EU. http://hdl.handle.net/20.500.12708/52590
• On the Use of Computer Vision for Numismatic Research / Zambanini, S., Kampel, M., & Schlapke, M. (2008). On the Use of Computer Vision for Numismatic Research. In Proceedings of the 9th International Symposium on Virtual Reality, Archaeology and Cultural Heritage (VAST’08). 9th International Symposium on Virtual reality, Archaeology, and Cultural Heritage, Braga, Portugal, EU. http://hdl.handle.net/20.500.12708/52356
• Segmentation of Ancient Coins Based on Local Entropy and Gray Value Range / Zambanini, S., & Kampel, M. (2008). Segmentation of Ancient Coins Based on Local Entropy and Gray Value Range. In J. Pers (Ed.), Proceedings of the 13th Computer Vision Winter Workshop (CVWW’08). http://hdl.handle.net/20.500.12708/52355

2007

• Automatic assessment of lesion development in hemangioma follow-up images / Zambanini, S. (2007). Automatic assessment of lesion development in hemangioma follow-up images [Master Thesis, Technische Universität Wien]. reposiTUm. http://hdl.handle.net/20.500.12708/179412
• Image based recognition of ancient coins / Zaharieva, M., Kampel, M., & Zambanini, S. (2007). Image based recognition of ancient coins. In W. Kropatsch, M. Kampel, & A. Hanbury (Eds.), Computer Analysis of Images and Patterns (pp. 547–554). Springer Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/51975
• Image based recognition of coins -- An Overview of the COINS project / Zaharieva, M., Kampel, M., & Zambanini, S. (2007). Image based recognition of coins -- An Overview of the COINS project. In Performance Evaluation for Computer Vision 31st AAPR/OAGM Workshop 2007 (pp. 57–64). http://hdl.handle.net/20.500.12708/51821
• Automatic Robust Registration of Cutaneous Hemangiomas for Follow-up Examinations / Zambanini, S., Langs, G., Sablatnig, R., Donath, P., & Maier, H. (2007). Automatic Robust Registration of Cutaneous Hemangiomas for Follow-up Examinations. In Performance Evaluation for Computer Vision 31st AAPR/OAGM Workshop 2007 (pp. 121–128). OCG. http://hdl.handle.net/20.500.12708/51818

2006

• Automatic Surveying of Cutaneous Hemangiomas / Zambanini, S., Langs, G., Sablatnig, R., Donath, P., & Maier, H. (2006). Automatic Surveying of Cutaneous Hemangiomas. In 18th International Conference on Pattern Recognition (pp. 1022–1025). http://hdl.handle.net/20.500.12708/51497

2005

• Segmentation and Surveying of Cutaneous Hemangiomas / Zambanini, S., Langs, G., & Bischof, H. (2005). Segmentation and Surveying of Cutaneous Hemangiomas. In A. Hanbury & H. Bischof (Eds.), Proceedings of Computer Vision Winter Workshop CVWW (pp. 103–112). Eigenverlag. http://hdl.handle.net/20.500.12708/51297

• Change detection in graffiti images / Dachs, F. (2024). Change detection in graffiti images [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2024.106190
  Download: PDF (8.48 MB)
• Learning 3D pose and target ID for accurate multi-target tracking / Sing, A. O. P. (2022). Learning 3D pose and target ID for accurate multi-target tracking [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.94901
  Download: PDF (5.64 MB)
• Vehicle-focused super-resolution of remote sensing imagery / Wahrmann, P. M. M. (2021). Vehicle-focused super-resolution of remote sensing imagery [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.68780
  Download: PDF (5.46 MB)
• Single image super-resolution for SAR images / Dimitrov, P. (2021). Single image super-resolution for SAR images [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.88085
  Download: PDF (9.91 MB)
• Human-centric best image selection on photo series / Pointner, M. (2020). Human-centric best image selection on photo series [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2020.66802
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• Image analysis approaches for parasite detection on honeybees / Schurischuster, S. (2018). Image analysis approaches for parasite detection on honeybees [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2018.44820
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• Mobility analysis for frailty syndrome assessment / Doppelbauer, S. (2017). Mobility analysis for frailty syndrome assessment [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2017.40742
  Download: PDF (14.9 MB)
• Invariant image representations for object category-based image classification / Anwar, H. (2015). Invariant image representations for object category-based image classification [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2015.32010
  Download: PDF (22 MB)
• Multi-image morphing: summarizing visual information from similar image regions / Hödlmoser, S. (2014). Multi-image morphing: summarizing visual information from similar image regions [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2014.22114
  Download: PDF (15.4 MB)
• Automatically recognizing ancient Roman republican coin legends / Kavelar, A. (2012). Automatically recognizing ancient Roman republican coin legends [Diploma Thesis, Technische Universität Wien]. reposiTUm. http://hdl.handle.net/20.500.12708/160583

• Reading the legends of Roman Republican coins
  2014 / Notable Books and Articles in Computing of 2014 / USA / Website
• VSMM 2014 Best Paper Award - "Multi-Image Morphing: Summarizing Visual Information from Similar Ancient Coin Image Regions", Stefan Hödlmoser, Sebastian Zambanini and Martin Kampel
  2014 / 20th International Conference on Virtual Systems & Multimedia / China
• Top 10% Paper Award"A Rotation-Invariant Bag of Visual Words Model for Symbols Based Ancient Coin Classification"Hafeez Anwar, Sebastian Zambanini, Martin Kampel
  2014 / Organizing Committee of the 2014 IEEE International Conference on Image Processing, Paris, France / France
• Prip Preis
  2005 / Austria

Soon, this page will include additional information such as reference projects, activities as journal reviewer and editor, memberships in councils and committees, and other research activities.

Until then, please visit Sebastian Zambanini’s research profile in TISS .