Guillermo Gallego
Photo: SCIoI
Guillermo Gallego is Professor of Robotic Interactive Perception at Technische Universität Berlin and Einstein Center Digital Future (ECDF). For SCIoI, he works on computer vision and robotics. He focuses on robot perception and on optimization methods for interdisciplinary imaging and control problems. Inspired by the human visual system, he works toward improving the perception systems of artificial agents, endowing them with intelligence to transform raw sensor data into knowledge, to provide autonomy in changing environments.
Projects
Guillermo Gallego is member of Project 36.
Publications +
Gu, C., Learned-Miller, E., Gallego, G., Sheldon, D., & Bideau, P. (2021). The Spatio-Temporal Poisson Point process: A simple Model for the Alignment of Event Camera Data. International Conference on Computer Vision (ICCV), 13495–13504. https://doi.org/10.1109/ICCV48922.2021.01324
Hamann, F., & Gallego, G. (2022). Stereo Co-capture System for Recording and Tracking Fish with Frame- and Event Cameras. International Conference on Pattern Recognition (ICPR), Workshop on Visual observation and analysis of Vertebrate And Insect Behavior. https://arxiv.org/abs/2207.07332
Shiba, S., Klose, Y., Aoki, Y., & Gallego, G. (2024). Secrets of Event-based Optical Flow, Depth and Ego-motion Estimation by Contrast Maximization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1–18. https://github.com/tub-rip/event_based_optical_flow
Shiba, S., Aoki, Y., & Gallego, G. (2022). Secrets of Event-Based Optical Flow. European Conference on Computer Vision (ECCV), 628–645. https://doi.org/10.1007/978-3-031-19797-0_36
Wischow, M., Irmisch, P., Boerner, A., & Gallego, G. (2024). Real-Time Noise Source Estimation of a Camera Systemfrom an Image and Metadata. Advanced Intelligent Systems, 2300479, 1–15. https://doi.org/10.1002/aisy.202300479
Hamann, F., Ghosh, S., Martínez, I. J., Hart, T., Kacelnik, A., & Gallego, G. (2024). Low-power, Continuous Remote Behavioral Localization with Event Cameras. CVPR. https://doi.org/10.48550/arXiv.2312.03799
Zhang, Z., Yezzi, A., & Gallego, G. (2022). Formulating Event-based Image Reconstruction as a Linear Inverse Problem with Deep Regularization using Optical Flow. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/TPAMI.2022.3230727
Shiba, S., Aoki, Y., & Gallego, G. (2022). Fast Event-based Optical Flow Estimation by Triplet Matching. Signal Processing Letters, 29, 2712–2716. https://doi.org/10.1109/LSP.2023.3234800
Ghosh, S., & Gallego, G. (2022). Event-based Stereo Depth Estimation from Ego-motion using Ray Density Fusion. ECCVW Ego4D 2022. https://arxiv.org/abs/2210.08927
Shiba, S., Hamann, F., Aoki, Y., & Gallego, G. (2023). Event-based Background-Oriented Schlieren. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1–16. https://doi.org/10.1109/TPAMI.2023.3328188
Guo, S., & Gallego, G. (2024). CMax-SLAM: Event-based Rotational-Motion Bundle Adjustment and SLAM System using Contrast Maximization. IEEE Transactions on Robotics. https://doi.org/10.1109/TRO.2024.3378443
Shiba, S., Aoki, Y., & Gallego, G. (2022). A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework. Advanced Intelligent Systems, 11. https://doi.org/10.1002/aisy.202200251
