VR-Notes: A Perspective-Based, Multimedia Annotation System in Virtual Reality

Virtual reality (VR) has begun to emerge as a new technology in the commercial and research space, and many people have begun to utilize VR technologies in their workflows. To improve user productivity in these scenarios, annotation systems in VR allow users to capture insights and observations while in VR sessions. In the digital, 3D world of VR, we can design annotation systems to take advantage of these capabilities to provide a richer annotation viewing experience. I propose VR-Notes, a design for a new annotation system in VR that focuses on capturing the annotator\u27s perspective for both doodle annotations and audio annotations, as well as various features that improve the viewing experience of these annotations at a later time. Early results from my experiment showed that the VR-Notes doodle method required 53%, 44%, 51% less movement and 42%, 41%, 45% less rotation (head, left controller, and right controller respectively) when compared to a popular 3D freehand drawing method. Additionally, users preferred and scored the VR Notes doodle method higher when compared to the freehand drawing method

The determinants of farm investment and residential construction in post-reform China

The objective of this paper is to clarify, on the basis of detailed farm level data derived from recent surveys,the importance of factors related to tenure security, farm size and credit availability in constraining farmers'agricultural investment. In particular, a direct measure of farmers'perceptions regarding tenure security will be utilized, as well as information on transactions in the credit market. The next section provides a description of the study areas. It is followed by a discussion of factors affecting farm investment and a description of investment patterns in the study areas. A formal model of farmers'consumption and investment decisions, and an econometric analysis are then presented and results are interpreted. The last section summarizes the paper.Environmental Economics&Policies,Economic Theory&Research,Banks&Banking Reform,International Terrorism&Counterterrorism,Agricultural Knowledge&Information Systems

Combining Geometric and Topological Information for Boundary Estimation

A fundamental problem in computer vision is boundary estimation, where the goal is to delineate the boundary of objects in an image. In this paper, we propose a method which jointly incorporates geometric and topological information within an image to simultaneously estimate boundaries for objects within images with more complex topologies. We use a topological clustering-based method to assist initialization of the Bayesian active contour model. This combines pixel clustering, boundary smoothness, and potential prior shape information to produce an estimated object boundary. Active contour methods are knownto be extremely sensitive to algorithm initialization, relying on the user to provide a reasonable starting curve to the algorithm. In the presence of images featuring objects with complex topological structures, such as objects with holes or multiple objects, the user must initialize separate curves for each boundary of interest. Our proposed topologically-guided method can provide an interpretable, smart initialization in these settings, freeing up the user from potential pitfalls associated with objects of complex topological structure. We provide a detailed simulation study comparing our initialization to boundary estimates obtained from standard segmentation algorithms. The method is demonstrated on artificial image datasets from computer vision, as well as real-world applications to skin lesion and neural cellular images, for which multiple topological features can be identified.Comment: 38 pages with appendices, 15 figure

Credit's effect on productivity in Chinese agriculture : a microeconomic model of disequilibrium

Many government programs want to provide more credit to the farm sector to increase agricultural productivity. If the marginal effect on productivity is small, those resources might be put to better use elsewhere. The authors conducted an econometric analysis of the effect of credit on output supply which recognizies that credit markets are not necessarily at equilibrium - so that credit rationing and nonborrowing are both possible. Only about 37 percent of the farmers in the study area were constrained by inadequate formal credit. Informal credit sources provided funds for specific non-agricultural activities that were not fungible. The results indicate that one additional yuan of liquidity yielded 0.235 yuan of additional gross value of output. These results suggest that for the area of China covered in the study, a good part of the short-term credit may actually be used for consumption and investment. Two conclusions are suggested for evaluating the probable effect of expanding agricultural credit. First, not all farmers, and sometimes only a minority, are constrained in their farming operations by inadequate credit. And second, greater supplies of formal credit will be diverted in part to consumption, so the likely effect on output will be smaller than what one might expect if all funds are assumed to be used productively.Banks&Banking Reform,Financial Intermediation,International Terrorism&Counterterrorism,Economic Theory&Research,Environmental Economics&Policies

Nonparametric Multi-shape Modeling with Uncertainty Quantification

The modeling and uncertainty quantification of closed curves is an important problem in the field of shape analysis, and can have significant ramifications for subsequent statistical tasks. Many of these tasks involve collections of closed curves, which often exhibit structural similarities at multiple levels. Modeling multiple closed curves in a way that efficiently incorporates such between-curve dependence remains a challenging problem. In this work, we propose and investigate a multiple-output (a.k.a. multi-output), multi-dimensional Gaussian process modeling framework. We illustrate the proposed methodological advances, and demonstrate the utility of meaningful uncertainty quantification, on several curve and shape-related tasks. This model-based approach not only addresses the problem of inference on closed curves (and their shapes) with kernel constructions, but also opens doors to nonparametric modeling of multi-level dependence for functional objects in general.Comment: 66 pages, 20 figure

Neural Shape Compiler: A Unified Framework for Transforming between Text, Point Cloud, and Program

3D shapes have complementary abstractions from low-level geometry to part-based hierarchies to languages, which convey different levels of information. This paper presents a unified framework to translate between pairs of shape abstractions: $\textit{Text}$ $\Longleftrightarrow$ $\textit{Point Cloud}$ $\Longleftrightarrow$ $\textit{Program}$. We propose $\textbf{Neural Shape Compiler}$ to model the abstraction transformation as a conditional generation process. It converts 3D shapes of three abstract types into unified discrete shape code, transforms each shape code into code of other abstract types through the proposed $\textit{ShapeCode Transformer}$, and decodes them to output the target shape abstraction. Point Cloud code is obtained in a class-agnostic way by the proposed $\textit{Point}$VQVAE. On Text2Shape, ShapeGlot, ABO, Genre, and Program Synthetic datasets, Neural Shape Compiler shows strengths in $\textit{Text}$ $\Longrightarrow$ $\textit{Point Cloud}$, $\textit{Point Cloud}$ $\Longrightarrow$ $\textit{Text}$, $\textit{Point Cloud}$ $\Longrightarrow$ $\textit{Program}$, and Point Cloud Completion tasks. Additionally, Neural Shape Compiler benefits from jointly training on all heterogeneous data and tasks.Comment: project page: https://tiangeluo.github.io/projectpages/shapecompiler.htm