TY - CHAP A1 - Reichert, Hannes A1 - Hetzel, Manuel A1 - Schreck, Steven A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Sensor Equivariance by LiDAR Projection Images T2 - 2023 IEEE Intelligent Vehicles Symposium (IV) KW - Bildverarbeitung KW - Sensor Y1 - 2023 U6 - https://doi.org/https://doi.org/10.1109/IV55152.2023.10186817 SP - 1 EP - 6 PB - IEEE ER - TY - CHAP A1 - Hubert, Andreas A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Influence of Background Color on 6D Pose Tracking Accuracy T2 - 2024 International Conference on Engineering and Emerging Technologies (ICEET), 27-28 December 2024 KW - Maschinelles Lernen KW - Deep Learning Y1 - 2024 U6 - https://doi.org/10.1109/ICEET65156.2024.10913824 SP - 1 EP - 6 PB - IEEE ER - TY - CHAP A1 - Hetzel, Manuel A1 - Reichert, Hannes A1 - Reitberger, Günther A1 - Fuchs, Erich A1 - Doll, Konrad A1 - Sick, Bernhard T1 - The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset T2 - 2023 IEEE Intelligent Vehicles Symposium (IV) KW - Autonomes Fahrzeug KW - Sensortechnik Y1 - 2023 U6 - https://doi.org/https://doi.org/10.1109/IV55152.2023.10186776 SP - 1 EP - 7 PB - IEEE ER - TY - CHAP A1 - Köhler, Sebastian A1 - Goldhammer, Michael A1 - Bauer, Sebastian A1 - Doll, Konrad A1 - Brunsmann, Ulrich A1 - Dietmayer, Klaus T1 - Early Detection of the Pedestrian’s Intention to Cross the Street T2 - 15th International IEEE Conference on Intelligent Transportation Systems (ITSC 2012), Anchorage, Alaska, USA. KW - Fahrerassistenzsystem KW - Bildverarbeitung Y1 - 2012 UR - http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2012/Koehler12-EDO.pdf U6 - https://doi.org/10.1109/ITSC.2012.6338797 SP - 1759 EP - 1764 ER - TY - PAT A1 - Reichert, Hannes A1 - Doll, Konrad T1 - An image encoding method for recording projection information of two-dimensional projections KW - Bildsignal KW - Codierung KW - Bildgebendes Verfahren Y1 - 2023 ER - TY - CHAP A1 - Hetzel, Manuel A1 - Reichert, Hannes A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Reliable Probabilistic Human Trajectory Prediction for Autonomous Applications T2 - Computer Vision – ECCV 2024 Workshops, Milan, Italy, September 29–October 4, 2024, Proceedings, Part XVII KW - Autonomes System KW - Mensch-Maschine-Kommunikation Y1 - 2025 SN - 9783031915840 U6 - https://doi.org/https://doi.org/10.1007/978-3-031-91585-7_9 SN - 0302-9743 SP - 135 EP - 152 PB - Springer Nature CY - Cham ER - TY - CHAP A1 - Hetzel, Manuel A1 - Reichert, Hannes A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Smart Infrastructure: A Research Junction T2 - 2021 IEEE International Smart Cities Conference (ISC2) KW - Autonomes Fahrzeug KW - Kreuzung Y1 - 2021 U6 - https://doi.org/https://doi.org/10.1109/ISC253183.2021.9562809 SP - 1 EP - 4 PB - IEEE ER - TY - CHAP A1 - Goldhammer, Michael A1 - Köhler, Sebastian A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Track-Based Forecasting of Pedestrian Behavior by Polynomial Approximation and Multilayer Perceptrons T2 - Intelligent Systems and Applications - Extended and Selected Results from the SAI Intelligent Systems Conference (IntelliSys) 2015 N2 - We present an approach for predicting continuous pedestrian trajectories over a time horizon of 2.5 s by means of polynomial least squares approximation and multilayer perceptron (MLP) artificial neural networks. The training data are gathered from 1075 real urban traffic scenes with uninstructed pedestrians including starting, stopping, walking and bending in. The polynomial approximation provides an extraction of the principal information of the underlying time series in the form of the polynomial coefficients. It is independent of sensor parameters such as cycle time and robust regarding noise. Approximation and prediction can be performed very efficiently. It only takes 35 ms on an Intel Core i7 CPU. Test results show 28% lower prediction errors for starting scenes and 32% for stopping scenes in comparison to applying a constant velocity movement model. Approaches based on MLP without polynomial input or Support Vector Regression (SVR) models as motion predictor are outperformed as well. KW - Fußgänger KW - Verkehrsverhalten KW - Prognose Y1 - 2016 SN - 978-3-319-33386-1 SP - 259 EP - 279 PB - Springer International Publishing ER - TY - CHAP A1 - Kempf, Johannes A1 - Doll, Konrad T1 - Modulare Hardware-Software Bildverarbeitungsplattform am Beispiel einer Vordergrund-Hintergrundtrennung T2 - 45. MPC-Workshop, Albstadt-Sigmaringen KW - Field programmable gate array KW - Bildverarbeitung Y1 - 2011 UR - https://www.mpc-gruppe.de/de/workshopbaende.html?file=files/content/workshops-volums/MPC_Workshopband_45.pdf SN - 1868-9221 IS - 45 SP - 19 EP - 24 ER - TY - CHAP A1 - Weimer, Daniel A1 - Köhler, Sebastian A1 - Hellert, Christian A1 - Doll, Konrad A1 - Brunsmann, Ulrich A1 - Krzikalla, Roland T1 - GPU Architecture for Stationary Multisensor Pedestrian Detection at Smart Intersections T2 - IEEE Intelligent Vehicles Symposium, Baden Baden, Germany KW - Fahrerassistenzsystem KW - Bildverarbeitung Y1 - 2014 U6 - https://doi.org/10.1109/IVS.2011.5940411 SP - 89 EP - 94 PB - IEEE ER - TY - CHAP A1 - Schlotterbeck-Macht, Stefan A1 - Doll, Konrad A1 - Brunsmann, Ulrich T1 - Introducing Chip Design using Speed of Light T2 - 7th International CONCEIVE DESIGN IMPLEMENT OPERATE Conference Kopenhagen, Denmark KW - CMOS Y1 - 2014 U6 - https://doi.org/10.4122/1.1000054669 ER - TY - CHAP A1 - Köhler, Sebastian A1 - Doll, Konrad A1 - Brunsmann, Ulrich T1 - Videobasierte Erkennung von Fußgängerintentionen zur Steigerung der Verkehrssicherheit T2 - Messe-Exponat und Vortrag, Vision 2012, Stuttgart, 06.-08. November KW - Fußgängererkennung KW - Fahrerassistenzsystem KW - Bildverarbeitung Y1 - 2012 ER - TY - CHAP A1 - Goldhammer, Michael A1 - Brunsmann, Ulrich A1 - Doll, Konrad T1 - Verkehrssicherheitsforschung: Bildverabeitung an intelligenten Kreuzungen T2 - Messe-Exponat und Vortrag, Vision 2012, Stuttgart, 06.-08. November KW - Bildverarbeitung KW - Verkehrssicherheit Y1 - 2012 ER - TY - GEN A1 - Zindler, Klaus A1 - Doll, Konrad T1 - Starke Partner für eine starke Region BT - Bereichsvorstellung AUTOMOTIVE N2 - Vortrag KW - Kraftfahrzeugtechnik Y1 - 2014 ER - TY - CHAP A1 - Zindler, Klaus A1 - Geiß, Niklas A1 - Doll, Konrad A1 - Heinlein, Sven T1 - Real-Time Ego-Motion Estimation using Lidar and a Vehicle Model Based Extended Kalman Filter T2 - Proceedings of the IEEE 17th International Conference on Intelligent Transportation Systems (ITSC 2014), Qingdao, China, October 8-11, 2014 KW - Kraftfahrzeug KW - Kalman-Filter Y1 - 2014 U6 - https://doi.org/10.1109/ITSC.2014.6957728 VL - 2014 IS - Beitrag Nr. ThA6.1 SP - 431 EP - 438 PB - IEEE ER - TY - CHAP A1 - Kempf, Johannes A1 - Schmitt, Marc A1 - Bauer, Sebastian A1 - Brunsmann, Ulrich A1 - Doll, Konrad T1 - Real-Time Processing of High-Resolution Image Streams using a Flexible FPGA Platform T2 - Embedded World Conference, Nürnberg, Germany KW - real-time processing KW - Field programmable gate array KW - Eingebettetes System KW - Bildverarbeitung Y1 - 2012 ER - TY - CHAP A1 - Hahnle, Michael A1 - Saxen, Frerk A1 - Hisung, Matthias A1 - Brunsmann, Ulrich A1 - Doll, Konrad T1 - FPGA-Based Real-Time Pedestrian Detection on High-Resolution Images T2 - 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Portland, USA KW - Fahrerassistenzsystem KW - Fußgänger Y1 - 2013 SN - 978-0-7695-4990-3 U6 - https://doi.org/10.1109/CVPRW.2013.95 SN - 2160-7508 SP - 629 EP - 635 PB - IEEE ER - TY - JOUR A1 - Mehrjoo, Masoud A1 - Pacuraru, Alexander A1 - Krüger, Luise A1 - Beck, Florian A1 - Doll, Konrad A1 - Arba Mosquera, Samuel T1 - Peri-operative intrastromal corneal segmentation after creation of corneal cuts based on laser induced optical breakdown: A perspective study JF - Journal of the European Optical Society-Rapid Publications N2 - Refractive correction techniques, such as Lenticule Extraction and LASIK, are pivotal in corneal surgery. Precise morphological characterization is essential for identifying post-operative complications, which can be compromised by image noise and low contrast. This study introduces an automated image processing algorithm that integrates non-local denoising, the Sobel gradient method, and Bayesian optimization to accurately delineate lenticule volumes and flap surfaces. Validated on 60 ex vivo porcine eyes treated with the SCHWIND ATOS femtosecond laser, the algorithm demonstrated high accuracy compared to the manual gold standard while effectively reducing variability. KW - Hornhautchirurgie KW - Bildverarbeitung Y1 - 2025 U6 - https://doi.org/https://doi.org/10.1051/jeos/2025006 SN - 1990-2573 VL - 21 IS - 1 PB - EDP Sciences ER - TY - CHAP A1 - Hubert, Andreas A1 - Jung, Janis A1 - Doll, Konrad T1 - Exploiting Self-Imposed Constraints on RGB and LiDAR for Unsupervised Training T2 - Proceedings of the 2023 6th International Conference on Machine Vision and Applications N2 - Hand detection on single images is an intensively researched area, and reasonable solutions are already available today. However, fine-tuning detectors within a specific domain remains a tedious task. Unsupervised training procedures can reduce the effort required to create domain-specific datasets and models. In addition, different modalities of the same physical space, here color and depth data, represent objects differently and thus allow for exploitation. We introduce and evaluate a training pipeline to exploit the modalities in an unsupervised manner. The supervision is omitted by choosing suitable self-imposed constraints for the data source. We compare our training results with ground truth training results and show that with these modalities, the domain can be extended without a single annotation, e.g., for detecting colored gloves. KW - Maschinelles Sehen Y1 - 2023 U6 - https://doi.org/https://doi.org/10.1145/3589572.3589575 SP - 15 EP - 21 PB - ACM CY - New York, NY, USA ER - TY - CHAP A1 - Kreß, Viktor A1 - Zernetsch, Stefan A1 - Doll, Konrad A1 - Sick, Bernhard T1 - Pose Based Trajectory Forecast of Vulnerable Road Users T2 - IEEE Symposium Series on Computational Intelligence (SSCI) N2 - In this article, we investigate the use of 3D human poses for trajectory forecasting of vulnerable road users (VRUs), such as pedestrians and cyclists, in road traffic. The forecast is based on past movements of the respective VRU and an important aspect in driver assistance systems and autonomous driving, which both could increase VRU safety. The 3D poses represent the entire body posture of the VRUs and can therefore provide important indicators for trajectory forecasting. In particular, we investigate the influence of different joint combinations and input sequence lengths of past movements on the accuracy of trajectory forecasts for pedestrians and cyclists. In addition, we divide VRU movements into the motion types wait, start, move, and stop and evaluate the results separately for each of them. Comparing it to an existing, solely head based trajectory forecast, we show the advantages of using 3D poses. With an input sequence length of 1.0 s, the forecasting error is reduced by 17.9 % for starting, 8.18 % for moving, and 11.0 % for stopping cyclists. For pedestrians, the error is reduced by 6.93 %, 2.73 %, and 5.02 %, respectively. With shorter input sequences, the improvements over the solely head based method remain for cyclists and even increase for pedestrians. KW - Fahrerassistenzsystem KW - Fußgänger KW - Radfahrer Y1 - 2019 U6 - https://doi.org/10.1109/SSCI44817.2019.9003023 VL - 2019 SP - 1200 EP - 1207 PB - IEEE CY - Xiamen, China ER - TY - CHAP A1 - Köhler, Sebastian A1 - Schreiner, Brian A1 - Ronalter, Steffen A1 - Doll, Konrad A1 - Brunsmann, Ulrich A1 - Zindler, Klaus T1 - Autonomous Evasive Maneuvers Triggered by Infrastructure-Based Detection of Pedestrian Intentions T2 - IEEE Intelligent Vehicles Symposium (IV' 13), Gold Coast, Australien, 23.-26. Juni KW - Evasive Maneuvers KW - Fahrerassistenzsystem KW - Bildverarbeitung Y1 - 2013 U6 - https://doi.org/10.1109/IVS.2013.6629520 SN - 1931-0587 SP - 519 EP - 526 ER -