Optimizing Meetings-to-Room Assignment

This publication describes a system for improving the efficiency of meetings by automatically matching meetings with the most appropriate meeting room. To perform this matching, the system can calculate a cost for each meeting/room pairing. The system can utilize an integer programming model to evaluate a plurality of configurations, each configuration containing a different combination of meeting/room pairings. The configurations can be scored, and the system can select the configuration with the lowest total cost. The system then updates any meeting with a changed room

ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans

We introduce ScanComplete, a novel data-driven approach for taking an incomplete 3D scan of a scene as input and predicting a complete 3D model along with per-voxel semantic labels. The key contribution of our method is its ability to handle large scenes with varying spatial extent, managing the cubic growth in data size as scene size increases. To this end, we devise a fully-convolutional generative 3D CNN model whose filter kernels are invariant to the overall scene size. The model can be trained on scene subvolumes but deployed on arbitrarily large scenes at test time. In addition, we propose a coarse-to-fine inference strategy in order to produce high-resolution output while also leveraging large input context sizes. In an extensive series of experiments, we carefully evaluate different model design choices, considering both deterministic and probabilistic models for completion and semantic inference. Our results show that we outperform other methods not only in the size of the environments handled and processing efficiency, but also with regard to completion quality and semantic segmentation performance by a significant margin.Comment: Video: https://youtu.be/5s5s8iH0NF

Symmetry in 3D shapes - analysis and applications to model synthesis

Symmetry is an essential property of a shapes\u27 appearance and presents a source of information for structure-aware deformation and model synthesis. This thesis proposes feature-based methods to detect symmetry and regularity in 3D shapes and demonstrates the utilization of symmetry information for content generation. First, we will introduce two novel feature detection techniques that extract salient keypoints and feature lines for a 3D shape respectively. Further, we will propose a randomized, feature-based approach to detect symmetries and decompose the shape into recurring building blocks. Then, we will present the concept of docking sites that allows us to derive a set of shape operations from an exemplar and will produce similar shapes. This is a key insight of this thesis and opens up a new perspective on inverse procedural modeling. Finally, we will present an interactive, structure-aware deformation technique based entirely on regular patterns.Symmetrie ist eine essentielle Eigenschaft für das Aussehen eines Objekts und bietet eine Informationsquelle für strukturerhaltende Deformation und Modellsynthese. Diese Arbeit beschäftigt sich mit merkmalsbasierter Symmetrieerkennung in 3D-Objekten und der Synthese von 3D-Modellen mittels Symmetrieinformationen. Zunächst stellen wir zwei neue Verfahren zur Merkmalserkennung vor, die hervorstechende Punkte bzw. Linien in 3D-Objekten erkennen. Darauf aufbauend beschreiben wir einen randomisierten, merkmalsbasierten Ansatz zur Symmetrieerkennung, der ein Objekt in sich wiederholende Bausteine zerlegt. Des Weiteren führen wir ein Konzept zur Modifikation von Objekten ein, welches Andockstellen in Geometrie berechnet und zur Generierung von ähnlichen Objekten eingesetzt werden kann. Dieses Konzept eröffnet völlig neue Möglichkeiten für die Ermittlung von prozeduralen Regeln aus Beispielen. Zum Schluss präsentieren wir eine interaktive Technik zur strukturerhaltenden Deformation, welche komplett auf regulären Strukturen basiert

Using Computer Vision To Label And Search A Physical Space

Effective operation of a warehouse requires keeping track of the location of various assets within the physical environment. As various sensors are carried through the warehouse environment by operators, range data collected by the sensors over time can be used to reconstruct 2D and 3D representations of the space. This disclosure describes techniques to estimate the locations of Point-Of Interest (POIs) and Regions-Of-Interest (ROIs) within a physical environment such as a warehouse. The location estimates are generated using a combination of 2D visual search of images containing text labels and barcodes, 2D/3D environment reconstruction using sensor data, and estimated trajectory of sensors. Computer vision techniques are applied to visual data which is obtained from operational processes that generate images, such as feeds from stationary cameras, images from moving cameras, photos of the environment, etc

Slippage Features

In this report, we present a novel feature detection technique for unstructured point clouds. We introduce a generalized concept of geometric features that detects locally uniquely identifiable keypoints as centroids of area with locally minimal slippage. We extend the concept to multiple scales and extract features using multi-scale mean shift clustering. In order to validate matches between feature points, we employ a two stage technique that first sorts out unlikely matches, followed by an approximate alignment between remaining features by a rotational cross-correlation analysis and a local iterative closest point (ICP) registration. The resulting residuals are then used as final similarity measure. The proposed combination of techniques results in a robust and reliable correspondence detection technique that yields registration results in situations where previous techniques are not able to detect usable feature correspondences. We provide a detailed empirical analysis of the method, and apply the technique to global registration, symmetry detection and deformable matching problems

Commissioning of the vacuum system of the KATRIN Main Spectrometer

The KATRIN experiment will probe the neutrino mass by measuring the beta-electron energy spectrum near the endpoint of tritium beta-decay. An integral energy analysis will be performed by an electro-static spectrometer (Main Spectrometer), an ultra-high vacuum vessel with a length of 23.2 m, a volume of 1240 m^3, and a complex inner electrode system with about 120000 individual parts. The strong magnetic field that guides the beta-electrons is provided by super-conducting solenoids at both ends of the spectrometer. Its influence on turbo-molecular pumps and vacuum gauges had to be considered. A system consisting of 6 turbo-molecular pumps and 3 km of non-evaporable getter strips has been deployed and was tested during the commissioning of the spectrometer. In this paper the configuration, the commissioning with bake-out at 300{\deg}C, and the performance of this system are presented in detail. The vacuum system has to maintain a pressure in the 10^{-11} mbar range. It is demonstrated that the performance of the system is already close to these stringent functional requirements for the KATRIN experiment, which will start at the end of 2016.Comment: submitted for publication in JINST, 39 pages, 15 figure

Commissioning of the vacuum system of the KATRIN Main Spectrometer

The KATRIN experiment will probe the neutrino mass by measuring the beta-electron energy spectrum near the endpoint of tritium beta-decay. An integral energy analysis will be performed by an electro-static spectrometer (Main Spectrometer), an ultra-high vacuum vessel with a length of 23.2 m, a volume of 1240 m^3, and a complex inner electrode system with about 120000 individual parts. The strong magnetic field that guides the beta-electrons is provided by super-conducting solenoids at both ends of the spectrometer. Its influence on turbo-molecular pumps and vacuum gauges had to be considered. A system consisting of 6 turbo-molecular pumps and 3 km of non-evaporable getter strips has been deployed and was tested during the commissioning of the spectrometer. In this paper the configuration, the commissioning with bake-out at 300{\deg}C, and the performance of this system are presented in detail. The vacuum system has to maintain a pressure in the 10^{-11} mbar range. It is demonstrated that the performance of the system is already close to these stringent functional requirements for the KATRIN experiment, which will start at the end of 2016

The design, construction, and commissioning of the KATRIN experiment

The KArlsruhe TRItium Neutrino (KATRIN) experiment, which aims to make a direct and model-independent determination of the absolute neutrino mass scale, is a complex experiment with many components. More than 15 years ago, we published a technical design report (TDR) [1] to describe the hardware design and requirements to achieve our sensitivity goal of 0.2 eV at 90% C.L. on the neutrino mass. Since then there has been considerable progress, culminating in the publication of first neutrino mass results with the entire beamline operating [2]. In this paper, we document the current state of all completed beamline components (as of the first neutrino mass measurement campaign), demonstrate our ability to reliably and stably control them over long times, and present details on their respective commissioning campaigns

Commissioning of the vacuum system of the KATRIN Main Spectrometer

The KATRIN experiment will probe the neutrino mass by measuring the -electron energy spectrum near the endpoint of tritium -decay. An integral energy analysis will be performed by an electro-static spectrometer (“Main Spectrometer”), an ultra-high vacuum vessel with a length of 23.2 m, a volume of 1240m3, and a complex inner electrode system with about 120 000 individual parts. The strong magnetic field that guides the -electrons is provided by super-conducting solenoids at both ends of the spectrometer. Its influence on turbo-molecular pumps and vacuum gauges had to be considered. A system consisting of 6 turbo-molecular pumps and 3 km of non-evaporable getter strips has been deployed and was tested during the commissioning of the spectrometer. In this paper the configuration, the commissioning with bake-out at 300 C, and the performance of this system are presented in detail. The vacuum system has to maintain a pressure in the 10$^{-11}$ mbar range. It is demonstrated that the performance of the system is already close to these stringent functional requirements for the KATRIN experiment, which will start at the end of 2016