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

The modular structure of an ontology: Atomic decomposition

Extracting a subset of a given ontology that captures all the ontology’s knowledge about a specified set of terms is a well-understood task. This task can be based, for instance, on locality-based modules. However, a single module does not allow us to understand neither topicality, connectedness, structure, or superfluous parts of an ontology, nor agreement between actual and intended modeling. The strong logical properties of locality-based modules suggest that the family of all such modules of an ontology can support comprehension of the ontology as a whole. However, extracting that family is not feasible, since the number of localitybased modules of an ontology can be exponential w.r.t. its size. In this paper we report on a new approach that enables us to efficiently extract a polynomial representation of the family of all locality-based modules of an ontology. We also describe the fundamental algorithm to pursue this task, and report on experiments carried out and results obtained.

Value Prior to Processing of Oriented Strand Board Flakes Through Hot Water Extraction

Research has already shown that the extraction of a valuable hemicellulose-rich stream is a viable option for revenue generation in the pulp and paper industries. Applying the value prior to pulping concept to the composite panel industry is a natural extension. If a hemicellulose extraction is accomplished under the right conditions, a non-trivial amount of fine chemicals can be generated, while leaving the woody substrate structurally intact for production to traditional products, such as oriented strand board (OSB). According to literature, the removal of hemicellulose can increase the dimensional stability while decreasing the degradability of OSB panels. This research studied the effects of hemicellulose removal by hot water extraction on softwood OSB wood flakes. Three reaction hold temperatures (120, 140, 160 deg C) and three isothermal hold times (20, 40, 60 min) were investigated. This research focuses on the changes that occurred in the physical and chemical properties of the wood flakes after extraction at each condition, while characterizing and classifying changes that occur in the liquid phase hydrolysates. Results indicated the extraction of hemicellulose in quantifiable levels begins at 120 deg. C and 40 mins and cellulose extraction begins at 140 deg C, 40 mins. The level of extraction of lignocellulosic materials, the decrease of wood flake thickness, and the acidity of the recovered hydrolysates all increase with an increase in extraction severity. The most promising results in regards to industrial implementation of OSB flake extraction occur at an extraction temperature of 140 deg C and 20 mins, coupled with hydrolysate conversion to high value chemicals

High-Definition Optical Coherence Tomography for the in vivo Detection of Demodex Mites

Background: Demodex mites are involved in different skin diseases and are commonly detected by skin scrape tests or superficial biopsies. A new high-definition optical coherence tomography (HD-OCT) with high lateral and axial resolution in a horizontal (en-face) and vertical (slice) imaging mode might offer the possibility of noninvasive and fast in vivo examination of demodex mites. Methods: Twenty patients with demodex-related skin diseases and 20 age- and gender-matched healthy controls were examined by HD-OCT. Mites per follicle and follicles per field of view were counted and compared to skin scrape tests. Results: HD-OCT images depicted mites in the en-face mode as bright round dots in groups of 3-5 mites per hair follicle. In the patients with demodex-related disease, a mean number of 3.4 mites per follicle were detected with a mean number of 2.9 infested follicles per area of view compared to a mean of 0.6 mites in 0.4 infested follicles in the controls. The skin scrape tests were negative in 21% of the patients. Conclusion: The innovative HD-OCT enables fast and noninvasive in vivo recognition of demodex mites and might become a useful tool in the diagnosis and treatment monitoring of demodex-related skin diseases. Copyright (C) 2012 S. Karger AG, Base

Hazard Communication: A Review of the Science Underpinning the Art of Communication for Health and Safety

This report was commissioned by the United States Occupational Safety and Health Administration to review the state of scientific inquiry supporting our knowledge regarding key elements of chemical hazard communication programs: labeling, warnings, material safety data sheets, and worker training. This endeavor supports the international effort to harmonize laws, regulations, and consensus standards affecting the ways in which information about hazardous chemicals is communicated. The international effort can be divided into three major functions: classifying health and environmental hazards, classifying physical hazards; and communicating hazard information. This last component involves the determination of what information will be communicated to users regarding the hazards and appropriate protective measures, as well as the way in which it will be transmitted, i.e. through symbols, labels, standard phrases, and training

Visually Plausible Human-Object Interaction Capture from Wearable Sensors

In everyday lives, humans naturally modify the surrounding environmentthrough interactions, e.g., moving a chair to sit on it. To reproduce suchinteractions in virtual spaces (e.g., metaverse), we need to be able to captureand model them, including changes in the scene geometry, ideally fromego-centric input alone (head camera and body-worn inertial sensors). This isan extremely hard problem, especially since the object/scene might not bevisible from the head camera (e.g., a human not looking at a chair whilesitting down, or not looking at the door handle while opening a door). In thispaper, we present HOPS, the first method to capture interactions such asdragging objects and opening doors from ego-centric data alone. Central to ourmethod is reasoning about human-object interactions, allowing to track objectseven when they are not visible from the head camera. HOPS localizes andregisters both the human and the dynamic object in a pre-scanned static scene.HOPS is an important first step towards advanced AR/VR applications based onimmersive virtual universes, and can provide human-centric training data toteach machines to interact with their surroundings. The supplementary video,data, and code will be available on our project page athttp://virtualhumans.mpi-inf.mpg.de/hops/<br

Modeling Micro-Porous Surfaces for Secondary Electron Emission Control to Suppress Multipactor

This work seeks to understand how the topography of a surface can be engineered to control secondary electron emission (SEE) for multipactor suppression. Two unique, semi-empirical models for the secondary electron yield (SEY) of a micro-porous surface are derived and compared. The first model is based on a two-dimensional (2D) pore geometry. The second model is based on a three-dimensional (3D) pore geometry. The SEY of both models is shown to depend on two categories of surface parameters: chemistry and topography. An important parameter in these models is the probability of electron emissions to escape the surface pores. This probability is shown by both models to depend exclusively on the aspect ratio of the pore (the ratio of the pore height to the pore diameter). The increased accuracy of the 3D model (compared to the 2D model) results in lower electron escape probabilities with the greatest reductions occurring for aspect ratios less than two. In order to validate these models, a variety of micro-porous gold surfaces were designed and fabricated using photolithography and electroplating processes. The use of an additive metal-deposition process (instead of the more commonly used subtractive metal-etch process) provided geometrically ideal pores which were necessary to accurately assess the 2D and 3D models. Comparison of the experimentally measured SEY data with model predictions from both the 2D and 3D models illustrates the improved accuracy of the 3D model. For a micro-porous gold surface consisting of pores with aspect ratios of two and a 50% pore density, the 3D model predicts that the maximum total SEY will be one. This provides optimal engineered surface design objectives to pursue for multipactor suppression using gold surfaces

Representing Diversity In The Dish: Using Patient-Derived In Vitro Models To Recreate The Heterogeneity Of Neurological Disease

Neurological diseases, including dementias such as Alzheimer\u27s disease (AD) and fronto-temporal dementia (FTD) and degenerative motor neuron diseases such as amyotrophic lateral sclerosis (ALS), are responsible for an increasing fraction of worldwide fatalities. Researching these heterogeneous diseases requires models that endogenously express the full array of genetic and epigenetic factors which may influence disease development in both familial and sporadic patients. Here, we discuss the two primary methods of developing patient-derived neurons and glia to model neurodegenerative disease: reprogramming somatic cells into induced pluripotent stem cells (iPSCs), which are differentiated into neurons or glial cells, or directly converting (DC) somatic cells into neurons (iNeurons) or glial cells. Distinct differentiation techniques for both models result in a variety of neuronal and glial cell types, which have been successful in displaying unique hallmarks of a variety of neurological diseases. Yield, length of differentiation, ease of genetic manipulation, expression of cell-specific markers, and recapitulation of disease pathogenesis are presented as determining factors in how these methods may be used separately or together to ascertain mechanisms of disease and identify therapeutics for distinct patient populations or for specific individuals in personalized medicine projects

A comparative approach to confirm antibiotic-resistant microbes in the cryosphere

Antibiotic-resistant microbes pose one of the biggest challenges of the current century. While areas with proximity to human impact are closely studied, a lot is yet to learn about antimicrobial resistance in remote regions like the cryosphere. Nowadays, antibiotic (AB) resistance is considered a pollution that has reached the Earth’s most pristine areas. However, monitoring of resistant environmental bacteria therein faces several challenges that inhibit scientific progress in this field. Due to many cultivation-based antibiotic susceptibility tests being optimized for mesophilic pathogenic microorganisms, many researchers opt for expensive molecular biological approaches to detect antibiotic resistance in the cryosphere. However, some disadvantages of these methods prohibit effective comprehensive monitoring of resistant bacteria in pristine areas, hence we suggest established cultivation-based approaches when looking for antimicrobial resistance in the cryosphere. In this study, we compared two common antibiotic susceptibility tests and optimized them to meet the needs of psychrophilic microorganisms. The resulting cultures thereof originated from cryospheric habitats with differing anthropogenic impacts. The results show that these methods are applicable to detect antibiotic resistance in cryospheric habitats and could potentially increase the comparability between studies