Using Self-Contradiction to Learn Confidence Measures in Stereo Vision

Learned confidence measures gain increasing importance for outlier removal and quality improvement in stereo vision. However, acquiring the necessary training data is typically a tedious and time consuming task that involves manual interaction, active sensing devices and/or synthetic scenes. To overcome this problem, we propose a new, flexible, and scalable way for generating training data that only requires a set of stereo images as input. The key idea of our approach is to use different view points for reasoning about contradictions and consistencies between multiple depth maps generated with the same stereo algorithm. This enables us to generate a huge amount of training data in a fully automated manner. Among other experiments, we demonstrate the potential of our approach by boosting the performance of three learned confidence measures on the KITTI2012 dataset by simply training them on a vast amount of automatically generated training data rather than a limited amount of laser ground truth data.Comment: This paper was accepted to the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. The copyright was transfered to IEEE (https://www.ieee.org). The official version of the paper will be made available on IEEE Xplore (R) (http://ieeexplore.ieee.org). This version of the paper also contains the supplementary material, which will not appear IEEE Xplore (R

UAV Vermessung im Bergbau - Stand der Forschung und Ausblick

Die Herstellung von optisch realistischen und hochgenauen 3D Modellen stellt eine zentrale Frage im Bereich der geodätischen und markscheiderischen Forschung dar. Mit dem zusehenden Aufkommen unbemannter Flugsysteme haben sich photogrammetrische Messsysteme als erschwingliche und flexible Alternative etabliert, wobei zur Gewährleistung definierter Genauigkeiten und somit zur Verwendung vergleichbarer Systeme für vermessungstechnische Anwendungen eine sorgfältige Flugplanung, Durchführung und Auswertung unbedingte Erfordernisse sind. Im vorliegenden Beitrag wird einerseits auf die laufenden Forschungen zu Genauigkeit und Anwendbarkeit der UAV-basierten Vermessung im Bergbau eingegangen und andererseits werden zukünftige Forschungstendenzen aufgezeigt, wodurch in neue, bislang nicht erreichbare Anwendungsfelder, vorgedrungen werden könnte.Creating and visualizing realistic and accurate 3D models is a central ambition of research in the field of geodesy and mine surveying. Due to the increasing affordability of un-manned aerial vehicles (UAVs) photogrammetric systems have been well established as affordable and flexible alternative. In order to ensure a certain accuracy and thus to enable the usage for surveying applications, careful flight planning, implementation and evaluation are of special importance. This paper discusses the ongoing research on accuracy and applicability of UAV-based mine surveying as well as future research tendencies, whereby new, currently not achievable fields of application could be investigated

High-throughput roll-to-roll production of polymer biochips for multiplexed DNA detection in point-of-care diagnostics

Roll-to-roll UV nanoimprint lithography has superior advantages for high-throughput manufacturing of micro- or nano-structures on flexible polymer foils with various geometries and configurations. Our pilot line provides large-scale structure imprinting for cost-effective polymer biochips (4500 biochips/hour), enabling rapid and multiplexed detections. A complete high-volume process chain of the technology for producing structures like μ-sized, triangular optical out-couplers or capillary channels (width: from 1 μm to 2 mm, height: from 200 nm up to 100 μm) to obtain biochips (width: 25 mm, length: 75 mm, height: 100 μm to 1.5 mm) was described. The imprinting process was performed with custom-developed resins on polymer foils with resin thicknesses ranging between 125–190 μm. The produced chips were tested in a commercial point-of-care diagnostic system for multiplexed DNA analysis of methicillin resistant Staphylococcus aureus (e.g., mecA, mecC gene detections). Specific target DNA capturing was based on hybridisation between surface bound DNA probes and biotinylated targets from the sample. The immobilised biotinylated targets subsequently bind streptavidin–horseradish peroxidase conjugates, which in turn generate light upon incubation with a chemiluminescent substrate. To enhance the light out-coupling thus to improve the system performance, optical structures were integrated into the design. The limits-of-detection of mecA (25 bp) for chips with and without structures were calculated as 0.06 and 0.07 μM, respectively. Further, foil-based chips with fluidic channels were DNA functionalised in our roll-to-roll micro-array spotter following the imprinting. This straightforward approach of sequential imprinting and multiplexed DNA functionalisation on a single foil was also realised for the first time. The corresponding foil-based chips were able to detect mecA gene DNA sequences down to a 0.25 μM concentration.This research was supported by R2R BIOFLUIDICS project (http://www.r2r-biofluidics.eu/) under Horizon 2020 European Union (EU) Research and Innovation Programme with grant agreement no 646260. The research was also partially supported by NextGenMicrofluidics project (https:// www. nextgenmicrofluidics.eu/) under HORIZON2020 with grant agreement no 862092. The authors cordially thank Gerburg Schider & Gerhard Mohr, Markus Postl, Paul Patter and Alexander Wheeldon (JOANNEUM RESEARCH – Materials, Weiz, Austria) for revising the manuscript, preparing all the chip and R2R pilot line illustrations, taking the photographs and providing technical support, respectively. The authors are also grateful to Christian Wolf and Johannes Götz (JOANNEUM RESEARCH – Materials, Weiz, Austria) for their supports in the fluidic design and R2R UV-NIL structuring, respectively. We further kindly thank Alba Simon Munoz and Robert Fay (SCIENION AG, Berlin, Germany) for providing the illustration of the R2R micro-spotting line. PT specially thanks Ege Ozgun (NANOTAM, Bilkent University, Ankara, Turkey) for critically reading the manuscript

Nuclear versus mitochondrial DNA: evidence for hybridization in colobine monkeys

<p>Abstract</p> <p>Background</p> <p>Colobine monkeys constitute a diverse group of primates with major radiations in Africa and Asia. However, phylogenetic relationships among genera are under debate, and recent molecular studies with incomplete taxon-sampling revealed discordant gene trees. To solve the evolutionary history of colobine genera and to determine causes for possible gene tree incongruences, we combined presence/absence analysis of mobile elements with autosomal, X chromosomal, Y chromosomal and mitochondrial sequence data from all recognized colobine genera.</p> <p>Results</p> <p>Gene tree topologies and divergence age estimates derived from different markers were similar, but differed in placing <it>Piliocolobus/Procolobus </it>and langur genera among colobines. Although insufficient data, homoplasy and incomplete lineage sorting might all have contributed to the discordance among gene trees, hybridization is favored as the main cause of the observed discordance. We propose that African colobines are paraphyletic, but might later have experienced female introgression from <it>Piliocolobus</it>/<it>Procolobus </it>into <it>Colobus</it>. In the late Miocene, colobines invaded Eurasia and diversified into several lineages. Among Asian colobines, <it>Semnopithecus </it>diverged first, indicating langur paraphyly. However, unidirectional gene flow from <it>Semnopithecus </it>into <it>Trachypithecus </it>via male introgression followed by nuclear swamping might have occurred until the earliest Pleistocene.</p> <p>Conclusions</p> <p>Overall, our study provides the most comprehensive view on colobine evolution to date and emphasizes that analyses of various molecular markers, such as mobile elements and sequence data from multiple loci, are crucial to better understand evolutionary relationships and to trace hybridization events. Our results also suggest that sex-specific dispersal patterns, promoted by a respective social organization of the species involved, can result in different hybridization scenarios.</p

Using Self-Contradiction to Learn Confidence Measures in Stereo Vision

Learned confidence measures gain increasing impor- tance for outlier removal and quality improvement in stereo vision. However, acquiring the necessary training data is typically a tedious and time consuming task that involves manual interaction, active sensing devices and/or synthetic scenes. To overcome this problem, we propose a new, flexi- ble, and scalable way for generating training data that only requires a set of stereo images as input. The key idea of our approach is to use different view points for reason- ing about contradictions and consistencies between multi- ple depth maps generated with the same stereo algorithm. This enables us to generate a huge amount of training data in a fully automated manner. Among other experiments, we demonstrate the potential of our approach by boost- ing the performance of three learned confidence measures on the KITTI2012 dataset by simply training them on a vast amount of automatically generated training data rather than a limited amount of laser ground truth data

UAV-based Autonomous Image Acquisition with Multi-View Stereo Quality Assurance by Confidence Prediction

In this paper we present an autonomous system for acquiring close-range high-resolution images that maximize the quality of a later-on 3D reconstruction with respect to coverage, ground resolution and 3D uncertainty. In contrast to previous work, our system uses the already acquired images to predict the confidence in the output of a dense multi-view stereo approach without executing it. This confidence encodes the likelihood of a successful reconstruction with respect to the observed scene and potential camera constellations. Our prediction module runs in real-time and can be trained without any externally recorded ground truth. We use the confidence prediction for on-site Quality assurance and for planning further views that are tailored for a specific multi-view stereo approach with respect to the given scene. We demonstrate the capabilities of our approach with an autonomous Unmanned Aerial Vehicle (UAV) in a challenging outdoor scenario

UAV Vermessung im Bergbau - Stand der Forschung und Ausblick

Die Herstellung von optisch realistischen und hochgenauen 3D Modellen stellt eine zentrale Frage im Bereich der geodätischen und markscheiderischen Forschung dar. Mit dem zusehenden Aufkommen unbemannter Flugsysteme haben sich photogrammetrische Messsysteme als erschwingliche und flexible Alternative etabliert, wobei zur Gewährleistung definierter Genauigkeiten und somit zur Verwendung vergleichbarer Systeme für vermessungstechnische Anwendungen eine sorgfältige Flugplanung, Durchführung und Auswertung unbedingte Erfordernisse sind. Im vorliegenden Beitrag wird einerseits auf die laufenden Forschungen zu Genauigkeit und Anwendbarkeit der UAV-basierten Vermessung im Bergbau eingegangen und andererseits werden zukünftige Forschungstendenzen aufgezeigt, wodurch in neue, bislang nicht erreichbare Anwendungsfelder, vorgedrungen werden könnte.Creating and visualizing realistic and accurate 3D models is a central ambition of research in the field of geodesy and mine surveying. Due to the increasing affordability of un-manned aerial vehicles (UAVs) photogrammetric systems have been well established as affordable and flexible alternative. In order to ensure a certain accuracy and thus to enable the usage for surveying applications, careful flight planning, implementation and evaluation are of special importance. This paper discusses the ongoing research on accuracy and applicability of UAV-based mine surveying as well as future research tendencies, whereby new, currently not achievable fields of application could be investigated

Accuracy related research on the use of UAV in Mine Surveying

During the last decades photogrammetric computer vision systems have been well established in scientific and commercial applications. Recent developments in image-based 3D reconstruction systems, affordable high quality digital consumer grade cameras and especially the increasing availability of unmanned aerial vehicles (UAVs) in conjunction with automated multi-view processing pipelines have resulted in an easy way of acquiring mid- to large-scale spatial data and creating realistic, visually appealing and accurate 3D models. Multi-copter UAVs are bridging the gap between terrestrial and traditional aerial image acquisition and are therefore ideally suited to enable easy and safe data collection and inspection tasks in complex or hazardous environments like mining. The presented research deals with studies on the identification and quantification of relevant influencing parameters regarding the desired or achievable accuracy in the UAV -based photogrammetric mine surveying. Based on different case studies for applications in mining in particular, the redundancy (overlap) and the ground resolution of the images, as well as the camera network configuration, the calibration of the camera and the type and quality of the scaling or georegistration are investigated