Related papers: OptoTracker project proposal
Next-generation megawatt-scale neutrino beams open the way to studying neutrino-nucleus scattering using gaseous targets for the first time. This represents an opportunity to improve the knowledge of neutrino cross sections in the energy…
Optimizing charged-particle track reconstruction algorithms is crucial for efficient event reconstruction in Large Hadron Collider (LHC) experiments due to their significant computational demands. Existing track reconstruction algorithms…
Robust 6D pose estimation of novel objects under challenging illumination remains a significant challenge, often requiring a trade-off between accurate initial pose estimation and efficient real-time tracking. We present a unified framework…
Charged Particle Therapy is a technique for cancer treatment that exploits hadron beams, mostly protons and carbons. A critical issue is the monitoring of the dose released by the beam to the tumor and to the surrounding tissues. We present…
Plastic scintillator detectors are used in high energy physics as well as for diagnostic imaging in medicine, beam monitoring on hadron therapy, muon tomography, dosimetry and many security applications. To combine particle tracking and…
Autonomous driving systems require a quick and robust perception of the nearby environment to carry out their routines effectively. With the aim to avoid collisions and drive safely, autonomous driving systems rely heavily on object…
The ability to steer light propagation inside scattering media has long been sought-after due to its potential widespread applications. To form optical foci inside scattering media, the only feasible strategy is to guide photons by using…
A new imaging technique for $\alpha$-particles using a fast optical camera focused on a thin scintillator is presented. As $\alpha$-particles interact in a thin layer of LYSO fast scintillator, they produce a localized flash of light. The…
Dynamic 3D reconstruction and point tracking in videos are typically treated as separate tasks, despite their deep connection. We propose St4RTrack, a feed-forward framework that simultaneously reconstructs and tracks dynamic video content…
We propose and validate a method of anti-neutrino energy reconstruction for charged-current meson-less interactions on composite fully active targets containing hydrogen (such as hydrocarbon scintillator), which is largely free of the…
The reconstruction of charged particle trajectories is a crucial challenge of particle physics experiments as it directly impacts particle reconstruction and physics performances. To reconstruct these trajectories, different reconstruction…
Plastic scintillator detectors with three-dimensional granularity and sub-nanosecond time resolution offer simultaneous particle tracking, identification, and calorimetry. However, scaling to larger volumes and finer segmentation poses…
We describe the Hybrid seeding, a standalone pattern recognition algorithm aiming at finding charged particle trajectories for the LHCb upgrade. A significant improvement to the charged particle reconstruction efficiency is accomplished by…
Today, most methods for image understanding tasks rely on feed-forward neural networks. While this approach has allowed for empirical accuracy, efficiency, and task adaptation via fine-tuning, it also comes with fundamental disadvantages.…
We propose a light-weight and highly efficient Joint Detection and Tracking pipeline for the task of Multi-Object Tracking using a fully-transformer architecture. It is a modified version of TransTrack, which overcomes the computational…
The determination of charged particle trajectories (tracking) in collisions at the CERN Large Hadron Collider (LHC) is one of the most important aspects for event reconstruction at hadron colliders. This is especially true in the high…
Current state-of-the-art trackers only rely on a target appearance model in order to localize the object in each frame. Such approaches are however prone to fail in case of e.g. fast appearance changes or presence of distractor objects,…
To determine the 3D orientation and 3D location of objects in the surroundings of a camera mounted on a robot or mobile device, we developed two powerful algorithms in object detection and temporal tracking that are combined seamlessly for…
We propose a novel approach for joint 3D multi-object tracking and reconstruction from RGB-D sequences in indoor environments. To this end, we detect and reconstruct objects in each frame while predicting dense correspondences mappings into…
The tracking-by-detection paradigm is the mainstream in multi-object tracking, associating tracks to the predictions of an object detector. Although exhibiting uncertainty through a confidence score, these predictions do not capture the…