Automatic 3D human modeling: an initial stage towards 2-way inside interaction in mixed reality

3D human models play an important role in computer graphics applications from a wide range of domains, including education, entertainment, medical care simulation and military training. In many situations, we want the 3D model to have a visual appearance that matches that of a specific living person and to be able to be controlled by that person in a natural manner. Among other uses, this approach supports the notion of human surrogacy, where the virtual counterpart provides a remote presence for the human who controls the virtual character\u27s behavior. In this dissertation, a human modeling pipeline is proposed for the problem of creating a 3D digital model of a real person. Our solution involves reshaping a 3D human template with a 2D contour of the participant and then mapping the captured texture of that person to the generated mesh. Our method produces an initial contour of a participant by extracting the user image from a natural background. One particularly novel contribution in our approach is the manner in which we improve the initial vertex estimate. We do so through a variant of the ShortStraw corner-finding algorithm commonly used in sketch-based systems. Here, we develop improvements to ShortStraw, presenting an algorithm called IStraw, and then introduce adaptations of this improved version to create a corner-based contour segmentatiuon algorithm. This algorithm provides significant improvements on contour matching over previously developed systems, and does so with low computational complexity. The system presented here advances the state of the art in the following aspects. First, the human modeling process is triggered automatically by matching the participant\u27s pose with an initial pose through a tracking device and software. In our case, the pose capture and skeletal model are provided by the Microsoft Kinect and its associated SDK. Second, color image, depth data, and human tracking information from the Kinect and its SDK are used to automatically extract the contour of the participant and then generate a 3D human model with skeleton. Third, using the pose and the skeletal model, we segment the contour into eight parts and then match the contour points on each segment to a corresponding anchor set associated with a 3D human template. Finally, we map the color image of the person to the 3D model as its corresponding texture map. The whole modeling process only take several seconds and the resulting human model looks like the real person. The geometry of the 3D model matches the contour of the real person, and the model has a photorealistic texture. Furthermore, the mesh of the human model is attached to the skeleton provided in the template, so the model can support programmed animations or be controlled by real people. This human control is commonly done through a literal mapping (motion capture) or a gesture-based puppetry system. Our ultimate goal is to create a mixed reality (MR) system, in which the participants can manipulate virtual objects, and in which these virtual objects can affect the participant, e.g., by restricting their mobility. This MR system prototype design motivated the work of this dissertation, since a realistic 3D human model of the participant is an essential part of implementing this vision

Ionospheric VTEC anomalies before Ms7.1 Yushu earthquake

Abstract:Vertical total electron content is examined to check whether the Ms7.1 Yushu earthquake on April 14, 2010, may have caused any anomalous ionospheric changes. The result shows two TEC increases over the epicenter vicinity on April 1 and 5; these anomalies drifted from east to west, the latter across the whole China. The increase on April 5 was probably related to geomagnetic activity, whereas the one on April 1 may possibly be related to the Yushu earthquake

A ShortStraw-based algorithm for corner finding in sketch-based interfaces

We present IStraw, a corner finding technique based on the ShortStraw algorithm. This new algorithm addresses deficiencies with ShortStraw while maintaining its simplicity and efficiency. We also develop an extension for ink strokes containing curves and arcs. We compare our algorithm against ShortStraw and two other state of the art corner finding approaches, MergeCF and Sezgin\u27s scale space algorithm. Based on an all-or-nothing accuracy metric, IStraw shows significant improvements over these algorithms for ink strokes with and without curves. (C) 2010 Elsevier Ltd. All rights reserved

Revisiting ShortStraw

We present IStraw, a new corner finding technique based on an analysis of the ShortStraw algorithm. Our analysis reveals several limitations in ShortStraw and we develop techniques to overcome them. We also present an extension to our corner finding approach for dealing with ink strokes that contain curves and arcs. An evaluation of our approach shows significant accuracy improvements over ShortStraw for polyline ink strokes with and without curves using an all-or-nothing accuracy metric while still maintaining ShortStraw\u27s computational complexity

Revisiting Shortstraw - Improving Corner Finding In Sketch-Based Interfaces

We present IStraw, a new corner finding technique based on an analysis of the ShortStraw algorithm. Our analysis reveals several limitations in ShortStraw and we develop techniques to overcome them. We also present an extension to our corner finding approach for dealing with ink strokes that contain curves and arcs. An evaluation of our approach shows significant accuracy improvements over ShortStraw for polyline ink strokes with and without curves using an all-or-nothing accuracy metric while still maintaining ShortStraw\u27s computational complexity

Photometric Display Calibration For Embedded Mr Environments

We demonstrate a new technique to minimize photometric differences between the color space of a display, sensor, and the real world, for mixed-reality (MR) systems where the real world is visible near or around a display. In this approach, we use an uncalibrated sensor to capture images of the display showing a series of calibration patterns. Using these images, we precompute a polynomial mapping function describing the continuous color-space transform between the real-world, sensor, and display. This mapping function can be evaluated in real-time to produce images that, when rendered on the embedded display, greatly reduce the color differences between displayed images of a mixed-reality world and the surrounding real-world environment. The color distribution of the resulting displayed images is significantly closer to that of the ground truth real-world scene as perceived through the human eye or other sensors. We demonstrate the impact of this technique when applied to a simple dynamic-geometry mixed-reality application. © 2013 IEEE

A Self-Tuning LCC/SP System for Electric Vehicle Wireless Charging against Large Self- and Mutual Inductance Variations

An LCC/SP self-tuning wireless charging system is proposed herein for use in a wireless charging test bench. With different dislocations in addition to changes in the coil self-inductance and mutual inductance caused by different secondary magnetic shielding materials, the system can ensure that the high power factor of the primary side remains unchanged without changing the circuit topology. Based on this normalized detuning LCC/SP circuit model, a switch-controlled capacitor (SCC) self-tuning method based on PI control is proposed. The control scheme employs only two MOSFETs and capacitors, without WIFI communication or parameter identification. A 2 kW experimental device was set up in the laboratory, and experimental verification was carried out with large-scale dislocations and different secondary magnetic shielding materials. The experimental results confirm that the system can maintain a high power factor (>0.9) under a system mutual inductance variation of 47.7% and secondary coil self-inductance variation of 12%, and that it can be applied in electric vehicle wireless chargers or high-power wireless charger test benches

The Chemical Compatibility of Sand–Attapulgite Cut-Off Walls for Landfills

Soil–bentonite cut-off walls have been widely used to control landfill pollution but they do not have good chemical compatibility with landfill leachate. Attapulgite can be substituted for bentonite in landfill cut-off walls. However, little is known about the chemical compatibility of attapulgite cut-off walls and leachate. This study experimentally investigated the chemical compatibility of attapulgite cut-off wall specimens with organic and inorganic contaminants and found that a sand–attapulgite cut-off wall has good chemical compatibility with organic contaminants. A CaCl2 solution was used to represent inorganic contaminants, and chemical oxygen demand (COD) was used as an indicator of organic content. The hydraulic conductivity of the cut-off wall initially decreased and then increased to become approximately constant as Ca2+ concentration increased. Changes in COD concentration were divided into a decreasing stage (0–10,000 mg/L) and a constant stage (10,000–40,000 mg/L). The increase or decrease in hydraulic conductivity was by no more than one order of magnitude. The increase in the hydraulic conductivity of the sand–attapulgite cut-off wall is explained in terms of bound water content and pore structure. An increase in Ca2+ concentration decreased the bound water content of the cut-off wall while the CaCl2 solution increased macropore and mesopore volume and decreased small pore volume in the sand–attapulgite cut-off wall. The purpose of this study was to elucidate the chemical compatibility of a sand–attapulgite cut-off wall with organic and inorganic contaminants and to increase the understanding of the interactions between the cut-off wall and the contaminants. The results of this research are informative for improving the application, design, and construction of sand–attapulgite cut-off walls