Parametric editing of clothed 3D avatars

Easy editing of a clothed 3D human avatar is central to many practical applications. However, it is easy to produce implausible, unnatural looking results, since subtle reshaping or pose alteration of avatars requires global consistency and agreement with human anatomy. Here, we present a parametric editing system for a clothed human body, based on use of a revised SCAPE model. We show that the parameters of the model can be estimated directly from a clothed avatar, and that it can be used as a basis for realistic, real-time editing of the clothed avatar mesh via a novel 3D body-aware warping scheme. The avatar can be easily controlled by a few semantically meaningful parameters, 12 biometric attributes controlling body shape, and 17 bones controlling pose. Our experiments demonstrate that our system can interactively produce visually pleasing results.     

Using ICESat's Geoscience Laser Altimeter System (GLAS) to assess large-scale forest disturbance caused by hurricane Katrina

In 2005, hurricane Katrina resulted in a large disturbance to U.S. forests. Recent estimates of damage from hurricane Katrina have relied primarily on optical remote sensing and field data. This paper is the first large-scale study to use satellite-based lidar data to quantify changes in forest structure from that event. GLAS data for the years prior to and following hurricane Katrina were compared to wind speed, forest cover, and damage data to assess the adequacy of sensor sampling, and to estimate changes in Mean Canopy Height (MCH) over all areas that experienced tropical force winds and greater. Statistically significant decreases in MCH post-Katrina were found to increase with wind intensity: Tropical Storm ?MCH = − 0.5 m, Category 1 ?MCH = − 2 m, and Category 2 ?MCH = − 4 m. A strong relationship was also found between changes in non-photosynthetic vegetation (?NPV), a metric previously shown to be related to storm damage, and post-storm MCH. The season of data acquisition was shown to influence calculations of MCH and MCH loss, but did not preclude the detection of major large-scale patterns of damage. Results from this study show promise for using space-borne lidar for large-scale assessments of forest disturbance, and highlight the need for future data on vegetation structure from space.     

Characterizing 3D vegetation structure from space: Mission requirements

Human and natural forces are rapidly modifying the global distribution and structure of terrestrial ecosystems on which all of life depends, altering the global carbon cycle, affecting our climate now and for the foreseeable future, causing steep reductions in species diversity, and endangering Earth's sustainability.To understand changes and trends in terrestrial ecosystems and their functioning as carbon sources and sinks, and to characterize the impact of their changes on climate, habitat and biodiversity, new space assets are urgently needed to produce high spatial resolution global maps of the three-dimensional (3D) structure of vegetation, its biomass above ground, the carbon stored within and the implications for atmospheric green house gas concentrations and climate. These needs were articulated in a 2007 National Research Council (NRC) report (NRC, 2007) recommending a new satellite mission, DESDynI, carrying an L-band Polarized Synthetic Aperture Radar (Pol-SAR) and a multi-beam lidar (Light RAnging And Detection) operating at 1064 nm. The objectives of this paper are to articulate the importance of these new, multi-year, 3D vegetation structure and biomass measurements, to briefly review the feasibility of radar and lidar remote sensing technology to meet these requirements, to define the data products and measurement requirements, and to consider implications of mission durations. The paper addresses these objectives by synthesizing research results and other input from a broad community of terrestrial ecology, carbon cycle, and remote sensing scientists and working groups. We conclude that:

(1)

Current global biomass and 3-D vegetation structure information is unsuitable for both science and management and policy. The only existing global datasets of biomass are approximations based on combining land cover type and representative carbon values, instead of measurements of actual biomass. Current measurement attempts based on radar and multispectral data have low explanatory power outside low biomass areas. There is no current capability for repeatable disturbance and regrowth estimates.

(2)

The science and policy needs for information on vegetation 3D structure can be successfully addressed by a mission capable of producing (i) a first global inventory of forest biomass with a spatial resolution 1 km or finer and unprecedented accuracy (ii) annual global disturbance maps at a spatial resolution of 1 ha with subsequent biomass accumulation rates at resolutions of 1 km or finer, and (iii) transects of vertical and horizontal forest structure with 30 m along-transect measurements globally at 25 m spatial resolution, essential for habitat characterization.

We also show from the literature that lidar profile samples together with wall-to-wall L-band quad-pol-SAR imagery and ecosystem dynamics models can work together to satisfy these vegetation 3D structure and biomass measurement requirements. Finally we argue that the technology readiness levels of combined pol-SAR and lidar instruments are adequate for space flight. Remaining to be worked out, are the particulars of a lidar/pol-SAR mission design that is feasible and at a minimum satisfies the information and measurement requirement articulated herein.     

Metrics for shot boundary detection in digital video sequences

The detection of shot boundaries in video sequences is an important task for generating indexed video databases. This paper provides a comprehensive quantitative comparison of the metrics that have been applied to shot boundary detection. In addition, several standardized statistical tests that have not been applied to this problem, as well as three new metrics, are considered. A mathematical framework for quantitatively comparing metrics is supplied. Experimental results based on a video database containing 39,000 frames are included.     

Towards the development of a virtual environment-based training system for mechanical assembly operations

In this paper, we discuss the development of Virtual Training Studio (VTS), a virtual environment-based training system that allows training supervisors to create training instructions and allows trainees to learn assembly operations in a virtual environment. Our system is mainly focused on the cognitive side of training so that trainees can learn to recognize parts, remember assembly sequences, and correctly orient the parts during assembly operations. Our system enables users to train using the following three training modes: (1) Interactive Simulation, (2) 3D Animation, and (3) Video. Implementing these training modes required us to develop several new system features. This paper presents an overview of the VTS system and describes a few main features of the system. We also report user test results that show how people train using our system. The user test results indicate that the system is able to support a wide variety of training preferences and works well to support training for assembly operations.

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Fast and effective feature-preserving mesh denoising

We present a simple and fast mesh denoising method, which can remove noise effectively, while preserving mesh features such as sharp edges and corners. The method consists of two stages. Firstly, noisy face normals are filtered iteratively by weighted averaging of neighboring face normals. Secondly, vertex positions are iteratively updated to agree with the denoised face normals. The weight function used during normal filtering is much simpler than that used in previous similar approaches, being simply a trimmed quadratic. This makes the algorithm both fast and simple to implement. Vertex position updating is based on the integration of surface normals using a least-squares error criterion. Like previous algorithms, we solve the least-squares problem by gradient descent, but whereas previous methods needed user input to determine the iteration step size, we determine it automatically. In addition, we prove the convergence of the vertex position updating approach. Analysis and experiments show the advantages of our proposed method over various earlier surface denoising methods.     

Profiles of Random Trees: Limit Theorems for Random Recursive Trees and Binary Search Trees

We prove convergence in distribution for the profile (the number of nodes at each level), normalized by its mean, of random recursive trees when the limit ratio α of the level and the logarithm of tree size lies in [0,e). Convergence of all moments is shown to hold only for α ∈ [0,1] (with only convergence of finite moments when α ∈ (1,e)). When the limit ratio is 0 or 1 for which the limit laws are both constant, we prove asymptotic normality for α = 0 and a "quicksort type" limit law for α = 1, the latter case having additionally a small range where there is no fixed limit law. Our tools are based on the contraction method and method of moments. Similar phenomena also hold for other classes of trees; we apply our tools to binary search trees and give a complete characterization of the profile. The profiles of these random trees represent concrete examples for which the range of convergence in distribution differs from that of convergence of all moments.     

A structured marketplace for arbitrary services

Creating simple marketplaces with common rules, that enable the dynamic selection and consumption of functionality, is the missing link to allow small businesses to enter the cloud, not only as consumers, but also as vendors. In this paper, we present the concepts behind a hybrid service and process repository that can act as the foundation for such a marketplace, as well as a prototype that allowed us to test various real-world scenarios. The advantage of a hybrid service and process repository is that, it not only holds a flat list of services, but also exposes a generic set of use cases, that it obtains information on how specific services can be used to implement the use cases as well as information to select services at run-time according to customer’s goal functions.     

3D characterization of hot metallic shells during industrial forging

During industrial forging of hot metallic shells, it is necessary to regularly measure the dimensions of the parts, especially the inner and outer diameters and the thickness of the walls. A forging sequence lasts 2 h or more during which the diameter of the shell is regularly measured in order to decide when to stop the forging process. For better working conditions, for the safety of the blacksmiths, and for a faster and more accurate measurement, we have developed a novel system based on two commercially available time of flight laser scanners for the measurement of the diameters of hot cylindrical metallic shells during the forging process. The advantages of using laser scanners are that they can be placed very far from the hot shell, more than 15 m, while at the same time giving an accurate point cloud from which three-dimensional views of the shell can be reconstructed and diameter measurements done. Moreover, more accurate measurement is achieved in less time with the laser system than with the conventional method using a large ruler. The system has been successfully used to measure the diameters of hot cylindrical metallic shells.     

The smooth (tractor) operator: insights of knowledge engineering

The design of and training for complex systems requires in-depth understanding of task demands imposed on users. In this project, we used the knowledge engineering approach (Bowles et al., 2004) to assess the task of mowing in a citrus grove. Knowledge engineering is divided into four phases: (1) Establish goals. We defined specific goals based on the stakeholders involved. The main goal was to identify operator demands to support improvement of the system. (2) Create a working model of the system. We reviewed product literature, analyzed the system, and conducted expert interviews. (3) Extract knowledge. We interviewed tractor operators to understand their knowledge base. (4) Structure knowledge. We analyzed and organized operator knowledge to inform project goals. We categorized the information and developed diagrams to display the knowledge effectively. This project illustrates the benefits of knowledge engineering as a qualitative research method to inform technology design and training.