Improved Orientation Estimation and Detection with Hybrid Object Detection Networks for Automotive Radar

This paper presents novel hybrid architectures that combine grid- and point-based processing to improve the detection performance and orientation estimation of radar-based object detection networks. Purely grid-based detection models operate on a bird's-eye-view (BEV) projection of the input point cloud. These approaches suffer from a loss of detailed information through the discrete grid resolution. This applies in particular to radar object detection, where relatively coarse grid resolutions are commonly used to account for the sparsity of radar point clouds. In contrast, point-based models are not affected by this problem as they process point clouds without discretization. However, they generally exhibit worse detection performances than grid-based methods. We show that a point-based model can extract neighborhood features, leveraging the exact relative positions of points, before grid rendering. This has significant benefits for a subsequent grid-based convolutional detection backbone. In experiments on the public nuScenes dataset our hybrid architecture achieves improvements in terms of detection performance (19.7% higher mAP for car class than next-best radar-only submission) and orientation estimates (11.5% relative orientation improvement) over networks from previous literature.Comment: (c) 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Self-Supervised Velocity Estimation for Automotive Radar Object Detection Networks

This paper presents a method to learn the Cartesian velocity of objects using an object detection network on automotive radar data. The proposed method is self-supervised in terms of generating its own training signal for the velocities. Labels are only required for single-frame, oriented bounding boxes (OBBs). Labels for the Cartesian velocities or contiguous sequences, which are expensive to obtain, are not required. The general idea is to pre-train an object detection network without velocities using single-frame OBB labels, and then exploit the network's OBB predictions on unlabelled data for velocity training. In detail, the network's OBB predictions of the unlabelled frames are updated to the timestamp of a labelled frame using the predicted velocities and the distances between the updated OBBs of the unlabelled frame and the OBB predictions of the labelled frame are used to generate a self-supervised training signal for the velocities. The detection network architecture is extended by a module to account for the temporal relation of multiple scans and a module to represent the radars' radial velocity measurements explicitly. A two-step approach of first training only OBB detection, followed by training OBB detection and velocities is used. Further, a pre-training with pseudo-labels generated from radar radial velocity measurements bootstraps the self-supervised method of this paper. Experiments on the publicly available nuScenes dataset show that the proposed method almost reaches the velocity estimation performance of a fully supervised training, but does not require expensive velocity labels. Furthermore, we outperform a baseline method which uses only radial velocity measurements as labels.Comment: Accepted for presentation at the 2022 33rd IEEE Intelligent Vehicles Symposium (IV) (IV 2022), June 5-9, 2022, in Aachen, German

2D Detectors for Particle Physics and for Imaging Applications

The demands on detectors for particle detection as well as for medical and astronomical X-ray imaging are continuously pushing the development of novel pixel detectors. The state of the art in pixel detector technology to date are hybrid pixel detectors in which sensor and read-out integrated circuits are processed on different substrates and connected via high density interconnect structures. While these detectors are technologically mastered such that large scale particle detectors can be and are being built, the demands for improved performance for the next generation particle detectors ask for the development of monolithic or semi-monolithic approaches. Given the fact that the demands for medical imaging are different in some key aspects, developments for these applications, which started as particle physics spin-off, are becomming rather independent. New approaches are leading to novel signal processing concepts and interconnect technologies to satisfy the need for very high dynamic range and large area detectors. The present state in hybrid and (semi-)monolithic pixel detector development and their different approaches for particle physics and imaging application is reviewed

Investigations on the energy weighting technique in medical X-ray imaging with the Medipix2 detector

In dieser Arbeit wurden die Einsatzmöglichkeiten der Energiewichtung in der Röntgenbildgebung sowohl theoretisch als auch experimentell analyisert. Die Methode der Energiewichtung geht von energieauflösenden Detektoren aus. Die dadurch zusätzlich gewonnene Information soll in der Bildgebung gewinnbringend eingesetzt werden. Bei dem Verfahren der Wichtung wird aus dem Datensatz der energieaufgelösten Bilder mit Hilfe energieabhängiger Faktoren ein einziges Bild durch gewichtetes Aufsummieren generiert. Die Wichtungsfaktoren werden so gewählt, dass die Qualität dieses Bildes maximal ist. Der eingesetzte Medipix2-Detektor ist ein photonenzählender Röntgenpixeldetektor, der neben einer hohen Ortsauflösung auch Information über die Energie der detektierten Photonen liefert. Dessen Eigenschaften wurden im Rahmen der Arbeit eingehend experimentell untersucht. Neben der Energiekalibrierung stand vor allem die Optimierung der Bildqualität im Vordergrund.Für die Messungen wurde ein Röntgenmessstand aufgebaut und die Eigenschaften der Komponenten analysiert. Sowohl die Entwicklung eines Steuersystems für die Computertomographie als auch die korrekte geometrische Ausrichtung der einzelnen Bestandteile waren Voraussetzung für die Erstellung artefaktfreier Bilder. Mit Rechnungen und Simulationen konnte gezeigt werden, dass die Methode der Energiewichtung eine durchschnittliche Steigerung der Bildqualität von etwa 40% ermöglicht (bezogen auf integrierende Detektoren). Die Wichtungsfaktoren können für projektive Bildgebungsverfahren sehr gut durch die Funktion E^-3 genähert werden, ohne dass der SDNR-Gewinn vermindert wird. Ebenfalls positiv ist, dass die Energieauflösung des Detektors keinen starken Einfluss hat. Außerdem wurde ermittelt, wie die Wichtungsfaktoren bei Vorhandensein von Streustrahlung angepasst werden müssen, damit der Vorteil der Wichtung nicht verloren geht. Die experimentelle Anwendung der Energiewichtung wurde mit dem Medipix2-Detektor durchgeführt. Dabei traten vor allem zwei Probleme auf: Durch unkorrigierte Detektor-Inhomogenitäten enthalten die Aufnahmen nicht nur reines Quantenrauschen, sondern auch Rauschanteile, die vom Detektor verursacht sind. Zudem verfälschen die energiedispersiven Effekte des verwendeten Detektors die Information über die Photonenenergien sehr stark. Das erste Problem kann durch bessere Masken und eine sehr intensive Flatfield-Korrektur weitgehend unter Kontrolle gebracht werden. Die Auswirkungen der energiedispersiven Effekte konnten durch geschickte Wahl der Spektren und Schwellen vermindert werden. Dadurch wurde die praktische Umsetzung der Methode der Energiewichtung mit dem Medipix2-Detektor ermöglicht. Wird die Energiewichtung in der tomographischen Bildgebung eingesetzt, so muss das Zusammenführen der Daten nach dem Logarithmieren erfolgen, damit Aufhärtungsartefakte nicht verstärkt werden. Die im Gegensatz zur projektiven Wichtung andere Abhängigkeit der Wichtungsfaktoren wurde theoretisch hergeleitet und durch Simulationsergebnisse bestätigt. Für maximale Bildqualität müssen die Wichtungsfaktoren dem Produkt aus der Differenz der Schwächungskoeffizienten der betrachteten Materialien und der spektralen Intensität hinter dem Objekt entsprechen. Simulationen belegen, dass die so erstellten Schnittbilder frei von Aufhärtungsartefakten sind und ihre Bildqualität um etwa 20 bis 30% höher als bei integrierenden Detektoren ist. Mit dem CT-Aufbau und dem Medipix2-System als Detektor wurden tomographische Aufnahmen unterschiedlicher Objekte und Zielsetzungen erstellt. Das Auftreten von Ringartefakten ist auf unterschiedliches Zählverhalten der einzelnen Pixel zurückzuführen. Es wurde ein Verfahren zur Unterdrückung der Ringartefakte entwickelt, die erfolgreich das Auftreten der Artefakte verhindert. Das Auflösungsvermögen des Aufbaus wurde mit Hilfe kontrastreicher Objektstrukturen bestimmt. Die theoretische Auflösungsgrenze des Gesamtsystems wurde damit erreicht. Für den zukünftigen Einsatz der Methode der Energiewichtung stellt die notwendige Detektorentwicklung die größte Herausforderung dar. Neben der Entwicklung von weiteren Sensormaterialien, wie etwa Cadmiumtellurid, stellt die für viele Einsatzzwecke notwendige große aktive Fläche ein Problem dar. Neben diesen Problemen müssen für energieaufgelöste Bildgebung vor allem die Auswirkungen energiedispersiver Effekte verhindert werden. Dies wird in der nächsten Generation der Medipix-Detektoren in Angriff genommen. Abschließend kann resümiert werden, dass der Einsatz der Energiewichtung in der projektiven und tomographischen Röntgenbildgebung mehrere Vorteile bietet - in erster Linie die Dosisreduktion in der medizinischen Diagnostik. Die Anforderungen des Verfahrens werden von Detektoren der näheren Zukunft erfüllt werden, so dass die praktische Anwendung der Methode der Energiewichtung bald möglich sein wird.The aim of this thesis was the analysis of the usefulness of energy weighting technique in X-ray imaging. This evaluation was done theoretically and experimentally. The energy weighting technique is based on energy resolving detectors. By those detectors, additional information is gathered that can be used for enhancement of the image quality. The data of energy resolved images is multiplied by energy dependent factors and summarised into one single image. The factors used are chosen for maximum increase of image quality. The Medipix2 detector is a photon-counting X-ray pixel detector that not only provides a high spatial resolution but also information about the energy of detected photons. The tools and appliances needed for the analysis were set up or programmed in the course of this work. The Medipix2 detector was the focus of activities; its properties were thoroughly investigated. After testing and improving energy calibration to get energy resolved data, the enhancement of image quality was aimed at as the main objective. For the experiments, an X-ray imaging setup was designed, built and the components were characterised. The development of a control system for computed tomography as well as the exact alignment of the devices were both absolutely necessary for the reconstruction of images without artefacts. Calculations and simulations show the benefits of energy weighting: the enhancement of image quality averages out at about 40% compared with integrating detectors. This corresponds to a reduction of X-ray dose by a factor of 2. The factors for energy weighting can be approximated by E^-3 for projective imaging with no significant loss of image quality. As positive for the feasibility of energy weighting is the low demand on the detector's energy resolution. For good image results even with scattered radiation, the weighting factors can be adjusted, thus retaining the positive effects. Energy weighting in experiments was done using the Medipix2 detector. Mainly two problems occurred: detector noise and the energy of arriving photons spreading over several pixels, thus falsifying the information about photon energy. Due to the latter phenomenon, acquiring energy resolved data proved almost impossible. In the reconstructed images, detector noise can be reduced by extensive flatfield corrections. The effects of energy spreading were diminished by adroit selection of X-ray spectra and thresholds. With these improvements, energy weighting with the Medipix2 detector gave good results. For energy weighting in tomographic imaging, the logarithm of the data has to be taken first, before summarisation of the data; otherwise, beam hardening artefacts are intensified. Energy weighting factors for tomography are different from those for projective imaging; they were deduced theoretically and verified by simulations. For best image quality, the weighting factors equal the product of the difference between the attenuation coefficients of the different materials regarded with the spectral intensity behind the object. Images reconstructed in this way show no beam hardening artefacts, and their image quality is about 20 to 30% higher compared to integrating detectors. Using the Medipix2 detector in a CT setup, tomographic images of several objects were taken. Ring artefacts occurred due to remaining inhomogeneities of the detector. Flatfield correction reduces these artefacts, but does not lead to complete suppression; for this, an additional filtering procedure was developed, successfully preventing ring artefacts. Objects with strong contrasts were used to examine the detector's resolution properties. The theoretical maximum resolution was attained. Reduction of the resolution for low threshold values, due to energy spreading effects, was proven in experiments. For future use of energy weighting, for example for medical purposes, development of detectors with additional energy resolving properties is necessary. Besides the development of new sensor materials like cadmium telluride, one of the main problems is the large active detector area necessary for many purposes. Furthermore, energy spreading effects have to be reduced for good quality of energy resolved imaging. This will be realised in the next generation of Medipix. Use of energy weighting methods in projective X-ray imaging and tomographic X-ray imaging is a very promising approach, with most notably the possibility of a reduced dose in medical diagnostics. The technical requirements will soon be met by detectors, making the implementation of energy weighting feasible in the near futur

Improved tomographic reconstructions using adaptive time-dependent intensity normalization

An advanced intensity normalization technique is proposed, which allows ring and wave artefacts to be suppressed in tomographic images. This is applied to data from beamline 2-BM-B of the Advanced Photon Source