Scene Coordinate Regression with Angle-Based Reprojection Loss for Camera Relocalization

Image-based camera relocalization is an important problem in computer vision and robotics. Recent works utilize convolutional neural networks (CNNs) to regress for pixels in a query image their corresponding 3D world coordinates in the scene. The final pose is then solved via a RANSAC-based optimization scheme using the predicted coordinates. Usually, the CNN is trained with ground truth scene coordinates, but it has also been shown that the network can discover 3D scene geometry automatically by minimizing single-view reprojection loss. However, due to the deficiencies of the reprojection loss, the network needs to be carefully initialized. In this paper, we present a new angle-based reprojection loss, which resolves the issues of the original reprojection loss. With this new loss function, the network can be trained without careful initialization, and the system achieves more accurate results. The new loss also enables us to utilize available multi-view constraints, which further improve performance.Comment: ECCV 2018 Workshop (Geometry Meets Deep Learning

Digitale Technologien und Big Data - Neue Herausforderungen für die Medienpädagogik

Das Ziel dieser Arbeit ist es, zu erschließen, vor welchen Herausforderungen die Medienpädagogik angesichts der Auswirkungen von Big Data und Digitalen Technologien auf die Gesellschaft steht. Bislang hat die Medienpädagogik nur vereinzelt Stellung zu dieser neuartigen Situation bezogen. In dieser Arbeit werden definierte Ziele und Theorien der Medienpädagogik auf ihre Anschlussmöglichkeiten in Bezug auf die Besonderheiten Digitaler Technologien hin untersucht. Digitale Technologien und Big-Data-Anwendungen verändern die Art und Weise von Kommunikation, Bildungsprozessen, Arbeit und Alltagsorganisation. Ihre technologischen Strukturen machen es Internet-Unternehmen möglich, weltweit Informationen über digitale Kommunikationsprozesse in Form von Daten zu analysieren, in die Privatsphäre von Menschen einzudringen, sie zu kontrollieren, zu konditionieren und zu prägen. Behörden und Regierungen werten die von Konzernen gesammelten Daten zudem für ihre Zwecke aus. Dargestellt wird, wie Konzerne mit Big-Data-Technologien in das alltägliche Leben eindringen, die Grundprinzipien der Demokratie verletzten und gesellschaftliche Errungenschaften angreifen. Es wird untersucht, inwieweit Technologie als Herrschaftsinstrument eingesetzt wird und vorhandene Gesetze zum Schutz persönlicher Daten ausreichen. Die Medienpädagogik ist aufgefordert die Besonderheit dieser neuartigen Technologie zu zu berücksichtigen. Als Ziel ihrer Arbeit stellt die Medienpädagogik in Theorie und Praxis die Entfaltung des Menschen und der Gesellschaft in den Vordergrund und sie muss agieren, wenn diese Grundelemente extremen Einflussnahmen ausgesetzt werden. Herausgearbeitet wurde, dass die Medienpädagogik besonders zum Handeln aufgerufen ist, wenn Monopolisten demokratische Strukturen mit neuen Technologien aushöhlen, denen Menschen ausschließlich als Objekte von Kommerzialisierung und Überwachung dienen.The aim of this work is to outline the challenges facing media pedagogy in the light of the social effects of big data and digital technologies. Media pedagogy has hitherto addressed this new situation only occasionally. Defined aims and theories of media pedagogy are examined in reference to their applicability to the special characteristics of the digital technologies. Digital technologies and big-data applications are changing the nature of communication, education, work and the organisation of daily life. Their technological structures make it possible for Internet companies to analyse information about digital communication around the world, and to invade, control, condition and influence people’s privacy. Public authorities and governments also evaluate data gathered by companies for their own purposes. The work shows how the corporate use of big-data technologies pervades everyday life, violates the basic principles of democracy and weakens social attainments. It examines the extent to which technology is used as an instrument of power and whether existing laws provide adequate protection to personal data. Media pedagogy is challenged to take the special characteristics of these new technologies into account. Theory and practice of media pedagogy emphasise the development of the individual and society, and must respond when they are subject to extreme influences. The works shows that media pedagogy is particularly called to action when monopolies undermine democratic structures with new technologies for which people merely serve as objects of commercialisation and surveillance

Direct Image to Point Cloud Descriptors Matching for 6-DOF Camera Localization in Dense 3D Point Cloud

We propose a novel concept to directly match feature descriptors extracted from RGB images, with feature descriptors extracted from 3D point clouds. We use this concept to localize the position and orientation (pose) of the camera of a query image in dense point clouds. We generate a dataset of matching 2D and 3D descriptors, and use it to train a proposed Descriptor-Matcher algorithm. To localize a query image in a point cloud, we extract 2D keypoints and descriptors from the query image. Then the Descriptor-Matcher is used to find the corresponding pairs 2D and 3D keypoints by matching the 2D descriptors with the pre-extracted 3D descriptors of the point cloud. This information is used in a robust pose estimation algorithm to localize the query image in the 3D point cloud. Experiments demonstrate that directly matching 2D and 3D descriptors is not only a viable idea but also achieves competitive accuracy compared to other state-of-the-art approaches for camera pose localization

Downstream signalling and specific inhibition of c-MET/HGF pathway in small cell lung cancer: implications for tumour invasion

The c-MET receptor can be overexpressed, amplified, or mutated in solid tumours including small cell lung cancer (SCLC). In c-MET-overexpressing SCLC cell line NCI-H69, hepatocyte growth factor (HGF) dramatically induced c-MET phosphorylation at phosphoepitopes pY1230/1234/1235 (catalytic tyrosine kinase), pY1003 (juxtamembrane), and also of paxillin at pY31 (CRKL-binding site). We utilised a global proteomics phosphoantibody array approach to identify further c-MET/HGF signal transduction intermediates in SCLC. Strong HGF induction of specific phosphorylation sites in phosphoproteins involved in c-MET/HGF signal transduction was detected, namely adducin-α [S724], adducin-γ [S662], CREB [S133], ERK1 [T185/Y187], ERK1/2 [T202/Y204], ERK2 [T185/Y187], MAPKK (MEK) 1/2 [S221/S225], MAPKK (MEK) 3/6 [S189/S207], RB [S612], RB1 [S780], JNK [T183/Y185], STAT3 [S727], focal adhesion kinase (FAK) [Y576/S722/S910], p38α-MAPK [T180/Y182], and AKT1[S473] and [T308]. Conversely, inhibition of phosphorylation by HGF in protein kinase C (PKC), protein kinase R (PKR), and also CDK1 was identified. Phosphoantibody-based immunohistochemical analysis of SCLC tumour tissue and microarray established the role of c-MET in SCLC biology. This supports a role of c-MET activation in tumour invasive front in the tumour progression and invasion involving FAK and AKT downstream. The c-MET serves as an attractive therapeutic target in SCLC, as shown through small interfering RNA (siRNA) and selective prototype c-MET inhibitor SU11274, inhibiting the phosphorylation of c-MET itself and its downstream molecules such as AKT, S6 kinase, and ERK1/2. Investigation of mechanisms of invasion and, ultimately, metastasis in SCLC would be very useful with these signal transduction molecules

A BCR-ABL Mutant Lacking Direct Binding Sites for the GRB2, CBL and CRKL Adapter Proteins Fails to Induce Leukemia in Mice

The BCR-ABL tyrosine kinase is the defining feature of chronic myeloid leukemia (CML) and its kinase activity is required for induction of this disease. Current thinking holds that BCR-ABL forms a multi-protein complex that incorporates several substrates and adaptor proteins and is stabilized by multiple direct and indirect interactions. Signaling output from this highly redundant network leads to cellular transformation. Proteins known to be associated with BCR-ABL in this complex include: GRB2, c-CBL, p62DOK, and CRKL. These proteins in turn, link BCR-ABL to various signaling pathways indicated in cellular transformation. In this study we show that a triple mutant of BCR-ABL with mutations of the direct binding sites for GRB2, CBL, p62DOK and CRKL, is defective for transformation of primary hematopoietic cells in vitro and in a murine CML model, while it retains the capacity to induce IL-3 independence in 32D cells. Compared to BCR-ABL, the triple mutant's ability to activate the MAP kinase and PI3-kinase pathways is severely compromised, while STAT5 phosphorylation is maintained, suggesting that the former are crucial for the transformation of primary cells, but dispensable for transformation of factor dependent cell lines. Our data suggest that inhibition of BCR-ABL-induced leukemia by disrupting protein interactions could be possible, but would require blocking of multiple sites

An affordable, quality-assured community-based system for high-resolution entomological surveillance of vector mosquitoes that reflects human malaria infection risk patterns.

ABSTRACT: BACKGROUND: More sensitive and scalable entomological surveillance tools are required to monitor low levels of transmission that are increasingly common across the tropics, particularly where vector control has been successful. A large-scale larviciding programme in urban Dar es Salaam, Tanzania is supported by a community-based (CB) system for trapping adult mosquito densities to monitor programme performance. Methodology An intensive and extensive CB system for routine, longitudinal, programmatic surveillance of malaria vectors and other mosquitoes using the Ifakara Tent Trap (ITT-C) was developed in Urban Dar es Salaam, Tanzania, and validated by comparison with quality assurance (QA) surveys using either ITT-C or human landing catches (HLC), as well as a cross-sectional survey of malaria parasite prevalence in the same housing compounds. RESULTS: Community-based ITT-C had much lower sensitivity per person-night of sampling than HLC (Relative Rate (RR) [95% Confidence Interval (CI)] = 0.079 [0.051, 0.121], P < 0.001 for Anopheles gambiae s.l. and 0.153 [0.137, 0.171], P < 0.001 for Culicines) but only moderately differed from QA surveys with the same trap (0.536 [0.406,0.617], P = 0.001 and 0.747 [0.677,0.824], P < 0.001, for An. gambiae or Culex respectively). Despite the poor sensitivity of the ITT per night of sampling, when CB-ITT was compared with QA-HLC, it proved at least comparably sensitive in absolute terms (171 versus 169 primary vectors caught) and cost-effective (153US$versus 187US$ per An. gambiae caught) because it allowed more spatially extensive and temporally intensive sampling (4284 versus 335 trap nights distributed over 615 versus 240 locations with a mean number of samples per year of 143 versus 141). Despite the very low vectors densities (Annual estimate of about 170 An gambiae s.l bites per person per year), CB-ITT was the only entomological predictor of parasite infection risk (Odds Ratio [95% CI] = 4.43[3.027,7. 454] per An. gambiae or Anopheles funestus caught per night, P =0.0373). Discussion and conclusion CB trapping approaches could be improved with more sensitive traps, but already offer a practical, safe and affordable system for routine programmatic mosquito surveillance and clusters could be distributed across entire countries by adapting the sample submission and quality assurance procedures accordingly

Microdevices for extensional rheometry of low viscosity elastic liquids : a review

Extensional flows and the underlying stability/instability mechanisms are of extreme relevance to the efficient operation of inkjet printing, coating processes and drug delivery systems, as well as for the generation of micro droplets. The development of an extensional rheometer to characterize the extensional properties of low viscosity fluids has therefore stimulated great interest of researchers, particularly in the last decade. Microfluidics has proven to be an extraordinary working platform and different configurations of potential extensional microrheometers have been proposed. In this review, we present an overview of several successful designs, together with a critical assessment of their capabilities and limitations

Numerical solution of MHD slip flow of a nanofluid past a radiating plate with Newtonian heating : a lie group approach

In this paper, we have examined the magnetohydrodynamic flow of a nanofluid past a radiating sheet. The Navier velocity slip, Newtonian heating and passively controlled wall boundary conditions are considered. The governing equations are reduced into similarity equations with the help of Lie group. A collocation method is used for simulation. The influence of emerging parameters on velocity, temperature, nanoparticle volumetric fraction profiles, as well as on local skin friction factor and local Nusselt number are illustrated in detail. It is found that the friction (heat transfer rate) is lower (higher) for passively controlled boundary conditions as compared to the case of an actively controlled boundary condition. The magnetic field decreases both the skin friction and the rate of heat transfer. The findings are validated with existing results and found an excellent agreement. The model explores new applications in solar collectors with direct solar radiative input using magnetic nanofluids

Single-Image Depth Prediction Makes Feature Matching Easier

Good local features improve the robustness of many 3D re-localization and multi-view reconstruction pipelines. The problem is that viewing angle and distance severely impact the recognizability of a local feature. Attempts to improve appearance invariance by choosing better local feature points or by leveraging outside information, have come with pre-requisites that made some of them impractical. In this paper, we propose a surprisingly effective enhancement to local feature extraction, which improves matching. We show that CNN-based depths inferred from single RGB images are quite helpful, despite their flaws. They allow us to pre-warp images and rectify perspective distortions, to significantly enhance SIFT and BRISK features, enabling more good matches, even when cameras are looking at the same scene but in opposite directions.Comment: 14 pages, 7 figures, accepted for publication at the European conference on computer vision (ECCV) 202