Current understanding of point defects and diffusion processes in silicon

The effects of oxidation of Si which established that vacancies (V) and Si self interstitials (I) coexist in Si at high temperatures under thermal equilibrium and oxidizing conditions are discussed. Some essential points associated with Au diffusion in Si are then discussed. Analysis of Au diffusion results allowed a determination of the I component and an estimate of the V component of the Si self diffusion coefficient. A discussion of theories on high concentration P diffusion into Si is then presented. Although presently there still is no theory that is completely satisfactory, significant progresses are recently made in treating some essential aspects of this subject

Detail-Preserving Pooling in Deep Networks

Most convolutional neural networks use some method for gradually downscaling the size of the hidden layers. This is commonly referred to as pooling, and is applied to reduce the number of parameters, improve invariance to certain distortions, and increase the receptive field size. Since pooling by nature is a lossy process, it is crucial that each such layer maintains the portion of the activations that is most important for the network's discriminability. Yet, simple maximization or averaging over blocks, max or average pooling, or plain downsampling in the form of strided convolutions are the standard. In this paper, we aim to leverage recent results on image downscaling for the purposes of deep learning. Inspired by the human visual system, which focuses on local spatial changes, we propose detail-preserving pooling (DPP), an adaptive pooling method that magnifies spatial changes and preserves important structural detail. Importantly, its parameters can be learned jointly with the rest of the network. We analyze some of its theoretical properties and show its empirical benefits on several datasets and networks, where DPP consistently outperforms previous pooling approaches.Comment: To appear at CVPR 201

Carbon, oxygen and their interaction with intrinsic point defects in solar silicon ribbon material: A speculative approach

Some background information on intrinsic point defects is provided and on carbon and oxygen in silicon in so far as it may be relevant for the efficiency of solar cells fabricated from EFG ribbon material. The co-precipitation of carbon and oxygen and especially of carbon and silicon self interstitials are discussed. A simple model for the electrical activity of carbon-self-interstitial agglomerates is presented. The self-interstitial content of these agglomerates is assumed to determine their electrical activity and that both compressive stresses (high self-interstitial content) and tensile stresses (low self-interstitial content) give rise to electrical activity of the agglomerates. The self-interstitial content of these carbon-related agglomerates may be reduced by an appropriate high temperature treatment and enhanced by a supersaturation of self-interstitials generated during formation of the p-n junction of solar cells. Oxygen present in supersaturation in carbon-rich silicon may be induced to form SiO, precipitates by self-interstitials generated during phosphorus diffusion. It is proposed that the SiO2-Si interface of the precipates gives rise to a continuum of donor stables and that these interface states are responsible for at least part of the light inhancement effects observed in oxygen containing EFG silicon after phosphorus diffusion

Virtual Rephotography: Novel View Prediction Error for 3D Reconstruction

The ultimate goal of many image-based modeling systems is to render photo-realistic novel views of a scene without visible artifacts. Existing evaluation metrics and benchmarks focus mainly on the geometric accuracy of the reconstructed model, which is, however, a poor predictor of visual accuracy. Furthermore, using only geometric accuracy by itself does not allow evaluating systems that either lack a geometric scene representation or utilize coarse proxy geometry. Examples include light field or image-based rendering systems. We propose a unified evaluation approach based on novel view prediction error that is able to analyze the visual quality of any method that can render novel views from input images. One of the key advantages of this approach is that it does not require ground truth geometry. This dramatically simplifies the creation of test datasets and benchmarks. It also allows us to evaluate the quality of an unknown scene during the acquisition and reconstruction process, which is useful for acquisition planning. We evaluate our approach on a range of methods including standard geometry-plus-texture pipelines as well as image-based rendering techniques, compare it to existing geometry-based benchmarks, and demonstrate its utility for a range of use cases.Comment: 10 pages, 12 figures, paper was submitted to ACM Transactions on Graphics for revie

LR-CNN: Local-aware Region CNN for Vehicle Detection in Aerial Imagery

State-of-the-art object detection approaches such as Fast/Faster R-CNN, SSD, or YOLO have difficulties detecting dense, small targets with arbitrary orientation in large aerial images. The main reason is that using interpolation to align RoI features can result in a lack of accuracy or even loss of location information. We present the Local-aware Region Convolutional Neural Network (LR-CNN), a novel two-stage approach for vehicle detection in aerial imagery. We enhance translation invariance to detect dense vehicles and address the boundary quantization issue amongst dense vehicles by aggregating the high-precision RoIs' features. Moreover, we resample high-level semantic pooled features, making them regain location information from the features of a shallower convolutional block. This strengthens the local feature invariance for the resampled features and enables detecting vehicles in an arbitrary orientation. The local feature invariance enhances the learning ability of the focal loss function, and the focal loss further helps to focus on the hard examples. Taken together, our method better addresses the challenges of aerial imagery. We evaluate our approach on several challenging datasets (VEDAI, DOTA), demonstrating a significant improvement over state-of-the-art methods. We demonstrate the good generalization ability of our approach on the DLR 3K dataset.Comment: 8 page

3D Acquisition of Mirroring Objects using Striped Patterns

Objects with mirroring optical characteristics are left out of the scope of most 3D scanning methods. We present here a new automatic acquisition approach, shape-from-distortion, that focuses on that category of objects, requires only a still camera and a color monitor, and produces range scans (plus a normal and a reflectance map) of the target. Our technique consists of two steps: first, an improved environment matte is captured for the mirroring object, using the interference of patterns with different frequencies to obtain sub-pixel accuracy. Then, the matte is converted into a normal and a depth map by exploiting the self-coherence of a surface when integrating the normal map along different paths. The results show very high accuracy, capturing even smallest surface details. The acquired depth maps can be further processed using standard techniques to produce a complete 3D mesh of the object

EVALUATION OF SADDLE HEIGHT IN ELITE CYCLISTS

Proper bike fit is essential to prevent injuries and improve performance. Especially recreational cyclists, often short on experience, rely on professional adjustment for seating position. Common bike fitting methods use formulas based on rider anthropometrics, e.g. the LeMond method (pubic symphysis height [PSH] x 0.883) (LeMond, 1988) or the Hamley method (PSH x 1.09) (Hamley et al., 1967). Pruitt (2006) recommends the correct saddle height [SH] within a knee angle [KA] of 25-35°. The purpose of this study is to verify these methods in elite men and women cyclists for today’s application

Hybrid Sample-based Surface Rendering

The performance of rasterization-based rendering on current GPUs strongly depends on the abilities to avoid overdraw and to prevent rendering triangles smaller than the pixel size. Otherwise, the rates at which highresolution polygon models can be displayed are affected significantly. Instead of trying to build these abilities into the rasterization-based rendering pipeline, we propose an alternative rendering pipeline implementation that uses rasterization and ray-casting in every frame simultaneously to determine eye-ray intersections. To make ray-casting competitive with rasterization, we introduce a memory-efficient sample-based data structure which gives rise to an efficient ray traversal procedure. In combination with a regular model subdivision, the most optimal rendering technique can be selected at run-time for each part. For very large triangle meshes our method can outperform pure rasterization and requires a considerably smaller memory budget on the GPU. Since the proposed data structure can be constructed from any renderable surface representation, it can also be used to efficiently render isosurfaces in scalar volume fields. The compactness of the data structure allows rendering from GPU memory when alternative techniques already require exhaustive paging

New acquisition techniques for real objects and light sources in computer graphics

Accurate representations of objects and light sources in a scene model are a crucial prerequisite for realistic image synthesis using computer graphics techniques. This thesis presents techniques for the effcient acquisition of real world objects and real world light sources, as well as an assessment of the quality of the acquired models. Making use of color management techniques, we setup an appearance reproduction pipeline that ensures best-possible reproduction of local light reflection with the available input and output devices. We introduce a hierarchical model for the subsurface light transport in translucent objects, derive an acquisition methodology, and acquire models of several translucent objects that can be rendered interactively. Since geometry models of real world objects are often acquired using 3D range scanners, we also present a method based on the concept of modulation transfer functions to evaluate their accuracy. In order to illuminate a scene with realistic light sources, we propose a method to acquire a model of the near-field emission pattern of a light source with optical prefiltering. We apply this method to several light sources with different emission characteristics and demonstrate the integration of the acquired models into both, global illumination as well as hardware-accelerated rendering systems.Exakte Repräsentationen der Objekte und Lichtquellen in einem Modell einer Szene sind eine unerlässliche Voraussetzung für die realistische Bilderzeugung mit Techniken der Computergraphik. Diese Dissertation beschäftigt sich mit der effizienten Digitalisierung von realen Objekten und realen Lichtquellen. Dabei werden sowohl neue Digitalisierungstechniken als auch Methoden zur Bestimmung der Qualität der erzeugten Modelle vorgestellt. Wir schlagen eine Verarbeitungskette zur Digitalisierung und Wiedergabe der Farbe und Spekularität von Objekten vor, die durch Ausnutzung von Farbmanagementtechniken eine bestmögliche Wiedergabe des Objekts unter Verwendung der gegebenen Ein- und Ausgabegeräte ermöglicht. Wir führen weiterhin ein hierarchisches Modell für den Lichttransport im Inneren von Objekten aus durchscheinenden Materialien sowie eine zugehörige Akquisitionsmethode ein und digitalisieren mehrere reale Objekte. Die dabei erzeugten Modelle können in Echtzeit angezeigt werden. Die Geometrie realer Objekte spielt eine entscheidende Rolle in vielen Anwendungen und wird oftmals unter Verwendung von 3D Scannern digitalisiert. Wir entwickeln daher eine Methode zur Bestimmung der Genauigkeit eines 3D Scanners, die auf dem Konzept der Modulationstransferfunktion basiert. Um eine Szene mit realen Lichtquellen beleuchten zu können, schlagen wir ferner eine Methode zur Erfassung der Nahfeldabstrahlung eine Lichtquelle vor, bei der vor der Digitalisierung ein optischer Filterungsschritt durchgeführt wird. Wir wenden diese Methode zur Digitalisierung mehrerer Lichtquellen mit unterschiedlichen Abstrahlcharakteristika an und zeigen auf, wie die dabei erzeugten Modelle in globalen Beleuchtungsberechnungen sowie bei der Bildsynthese mittels moderner Graphikkarten verwendet werden können