A vision-based remote control

This Chapter presents a vision-based system for touch-free interaction with a display at a distance. A single camera is fixed on top of the screen and is pointing towards the user. An attention mechanism allows the user to start the interaction and control a screen pointer by moving their hand in a fist pose directed at the camera. On-screen items can be chosen by a selection mechanism. Current sample applications include browsing video collections as well as viewing a gallery of 3D objects, which the user can rotate with their hand motion. We have included an up-to-date review of hand tracking methods, and comment on the merits and shortcomings of previous approaches. The proposed tracker uses multiple cues, appearance, color, and motion, for robustness. As the space of possible observation models is generally too large for exhaustive online search, we select models that are suitable for the particular tracking task at hand. During a training stage, various off-the-shelf trackers are evaluated. From this data differentmethods of fusing them online are investigated, including parallel and cascaded tracker evaluation. For the case of fist tracking, combining a small number of observers in a cascade results in an efficient algorithm that is used in our gesture interface. The system has been on public display at conferences where over a hundred users have engaged with it. © 2010 Springer-Verlag Berlin Heidelberg.

Semantic Discriminant mapping for classification and browsing of remote sensing textures and objects

We present a new approach based on Discriminant Analysis to map a high dimensional image feature space onto a subspace which has the following advantages: 1. each dimension corresponds to a semantic likelihood, 2. an efficient and simple multiclass classifier is proposed and 3. it is low dimensional. This mapping is learnt from a given set of labeled images with a class groundtruth. In the new space a classifier is naturally derived which performs as well as a linear SVM. We will show that projecting images in this new space provides a database browsing tool which is meaningful to the user. Results are presented on a remote sensing database with eight classes, made available online. The output semantic space is a low dimensional feature space which opens perspectives for other recognition tasks. © 2005 IEEE.

Room-temperature remote-plasma sputtering of c-axis oriented zinc oxide thin films

Highly c-axis oriented ZnO films have been deposited at room temperature with high rates (∼50 nm·min -1) using an innovative remote plasma sputtering configuration, which allows independent control of the plasma density and the sputtering ion energy. The ZnO films deposited possess excellent crystallographic orientation, high resistivity (>10 9 Ω·m), and exhibit very low surface roughness. The ability to increase the sputtering ion energy without causing unwanted Ar + bombardment onto the substrate has been shown to be crucial for the growth of films with excellent c-axis orientation without the need of substrate heating. In addition, the elimination of the Ar + bombardment has facilitated the growth of films with very low defect density and hence very low intrinsic stress (100 MPa for 3 μm-thick films). This is over an order of magnitude lower than films grown with a standard magnetron sputtering system. © 2012 American Institute of Physics.

Visual pattern recognition models for remote sensing of civil infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Remote Wireless Communications for Construction Management: A Case Study

The recent advances in urban wireless communications and protocols that spurred the development of city-wide wireless infrastructure motivated this research, since in many cases, construction sites are not conveniently located for wired connectivity. Large scale transportation projects for example, such as new highways, railroad tracks and the networks of utilities (power-lines, phone lines, mobile towers, etc) that usually follow them are constructed in areas where wired infrastructure for data exchange is often expensive and time-consuming to deploy. The communication difficulties that can be encountered in such construction sites can be addressed with a wireless communications link between the construction site and the decision-making office. This paper presents a case study on long-range, wireless communications suitable for data exchange between construction sites and engineering headquarters. The purpose of this study was to define the requirements for a reliable wireless communications model where common types of electronic construction data will be exchanged in a fast and efficient manner, and construction site personnel will be able to interact and share knowledge, information and electronic resources with the office staff.

Visual Pattern Recognition Models for Remote Sensing of Civil Infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

High-density remote plasma sputtering of high-dielectric-constant amorphous hafnium oxide films

Hafnium oxide (HfOx) is a high dielectric constant (k) oxide which has been identified as being suitable for use as the gate dielectric in thin film transistors (TFTs). Amorphous materials are preferred for a gate dielectric, but it has been an ongoing challenge to produce amorphous HfOx while maintaining a high dielectric constant. A technique called high target utilization sputtering (HiTUS) is demonstrated to be capable of depositing high-k amorphous HfOx thin films at room temperature. The plasma is generated in a remote chamber, allowing higher rate deposition of films with minimal ion damage. Compared to a conventional sputtering system, the HiTUS technique allows finer control of the thin film microstructure. Using a conventional reactive rf magnetron sputtering technique, monoclinic nanocrystalline HfOx thin films have been deposited at a rate of ∼1.6nmmin-1 at room temperature, with a resistivity of 1013Ωcm, a breakdown strength of 3.5MVcm-1 and a dielectric constant of ∼18.2. By comparison, using the HiTUS process, amorphous HfOx (x=2.1) thin films which appear to have a cubic-like short-range order have been deposited at a high deposition rate of ∼25nmmin-1 with a high resistivity of 1014Ωcm, a breakdown strength of 3MVcm-1 and a high dielectric constant of ∼30. Two key conditions must be satisfied in the HiTUS system for high-k HfOx to be produced. Firstly, the correct oxygen flow rate is required for a given sputtering rate from the metallic target. Secondly, there must be an absence of energetic oxygen ion bombardment to maintain an amorphous microstructure and a high flux of medium energy species emitted from the metallic sputtering target to induce a cubic-like short range order. This HfOx is very attractive as a dielectric material for large-area electronic applications on flexible substrates. A remote plasma sputtering process (high target utilization sputtering, HiTUS) has been used to deposit amorphous hafnium oxide with a very high dielectric constant (∼30). X-ray diffraction shows that this material has a microstructure in which the atoms have a cubic-like short-range order, whereas radio frequency (rf) magnetron sputtering produced a monoclinic polycrystalline microstructure. This is correlated to the difference in the energetics of remote plasma and rf magnetron sputtering processes. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deposition of low stress amorphous zinc tin oxide at ambient temperature using a remote plasma sputtering process suitable for delicate substrates

ZnxSnyOz thin films (<100nm thickness), deposited by remote sputtering from a metal target using a confined argon plasma and oxygen gas jet near the sample, were investigated for their material properties. No visible deformation or curl was observed when deposited on plastic. Materials were confirmed to be amorphous and range between 5 and 10 at.% Sn concentration by x-ray diffraction, x-ray photoemission spectroscopy and energydispersive x-ray spectroscopy. Factors affecting the material composition over time are discussed. Depletion of the Sn as the target ages is suspected. © The Electrochemical Society.