Julian Strohmayer is a research assistant and PhD student at the Computer Vision Lab (CVL), Institute of Visual Computing & Human-Centered Technology, TU Wien, Austria. He received his BSc degree in Media Informatics and Visual Computing in 2018 and his MSc (Dipl.-Ing.) degree in Visual Computing in 2020, both from TU Wien. His current research interests include human activity recognition and behavior modeling using unconventional multimodal computer vision systems. He is currently working on the Blindsight project.
Profiles
ResearchGate | Google Scholar | SemanticScholar | ORCID
Publications
Strohmayer, J., Kampel, M. (2023). WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32. In: Christensen, H.I., Corke, P., Detry, R., Weibel, JB., Vincze, M. (eds) Computer Vision Systems. ICVS 2023. Lecture Notes in Computer Science, vol 14253. Springer, Cham. https://doi.org/10.1007/978-3-031-44137-0_4
Strohmayer, J., Kampel, M. (2023). Domain-Adaptive Data Synthesis for Large-Scale Supermarket Product Recognition. In: Tsapatsoulis, N., et al. Computer Analysis of Images and Patterns. CAIP 2023. Lecture Notes in Computer Science, vol 14184. Springer, Cham. https://doi.org/10.1007/978-3-031-44237-7_23.
Strohmayer J. and Kampel M., “Real-Time Supermarket Product Recognition on Mobile Devices Using Scalable Pipelines,” 2023 IEEE International Conference on Image Processing (ICIP), Kuala Lumpur, Malaysia, October 2023, pp. 420-424, doi: https://doi.org/10.1109/ICIP49359.2023.10223137.
Strohmayer J. and Kampel M., “Blind Modalities for Human Activity Recognition.” In Assistive Technology: Shaping a Sustainable and Inclusive World, pp. 89-96. IOS Press, August 2023, doi: https://doi.org/10.3233/SHTI230601.
Strohmayer J. and Kampel M., “A Compact Tri-modal Camera Unit for RGBDT Vision”, In the Proceedings of the 5th International Conference on Machine Vision and Applications (ICMVA), February 2022, Singapore, Singapore, doi: https://doi.org/10.1145/3523111.3523116.
Strohmayer J. and Kampel M., “Data Synthesis for Large-scale Supermarket Product Recognition”, In the Proceedings of the Austrian Association for Pattern Recognition (OAGM) Joint Austrian Computer Vision and Robotics Workshop, November 2021, St. Pölten, Austria, doi: https://doi.org/10.3217/978-3-85125-869-1-11.
Strohmayer J., Knapp J. and Kampel M., “Efficient Models for Real-Time Person Segmentation on Mobile Phones”, In the Proceedings of the 29th European Signal Processing Conference (EUSIPCO), May 2021, Dublin, Ireland, doi: https://doi.org/10.23919/EUSIPCO54536.2021.9616237.
Pramerdorfer C., Strohmayer J. and Kampel M., “Sdt: A Synthetic Multi-Modal Dataset For Person Detection And Pose Classification”, In the Proceedings of the 2020 IEEE International Conference on Image Processing (ICIP), October 2020, Abu Dhabi, United Arab Emirates, doi: https://doi.org/10.1109/ICIP40778.2020.9191284.
Strohmayer J., “Multi-modal Fusion of Depth and Thermal Images for Human Behavior Modeling”, Diploma Thesis, Technische Universität Wien, March 2020, Advisor Martin Kampel, doi: https://doi.org/10.34726/hss.2020.66201.
Presentations
Strohmayer J. and Kampel M., “Real-time Supermarket Product Recognition on Mobile Devices using Scalable Pipelines”, In the 26th Computer Vision Winter Workshop (CVWW), February 2023, Krems, Austria. (in-person oral presentation, out of proceedings)
Datasets
WiFi CSI Long-Range Through-Wall Activities
Synthetic Supermarket Product Recognition Datasets
Synthetic Depth & Thermal (SDT) Dataset