Perceiving virtual geographic slant: action influences perception

technical reportFour experiments varied the extent and nature of observer movement in a virtual environment to examine the influence of action on estimates of geographical slant. Previous slant studies demonstrated that people consciously overestimate hill slant but can still accurately guide an action toward the hill (Proffitt, Bhalla, Gossweiler & Midget, 1995). Related studies (Bhalla & Proffitt, 1999) suggest that one s potential to act may influence perception of slant and that distinct representations may independently inform perceptual and motoric responses. We found that in all conditions, perceptual judgments were overestimated and motoric adjustments were more accurate. The virtual environment allowed manipulation of the effort required to walk up simulated hills. Walking with the effort appropriate to the visual slant led to increased perceptual overestimation of slant compared to active walking with effort appropriate to level ground, while visually guided actions remained accurate

Procedural Reproduction of Terrain Textures with Geographic Data

International audienceSurface textures of high resolution and quality, either acquired from aerial or satellite imagery or computed using procedural models, are crucial for photorealistic terrain rendering. Procedural models provide a compact representation and can be evaluated at run-time. In this paper we present an extension to an existing, GPU-friendly procedural texturing model, such that it can be fitted semiautomatically to real-world data. In order to increase realism and to account for geographic conditions, we also include temperature, solar radiation and rainfall distributions - simulated ormodeled using measured data from gaging stations - into the reproduction process. The original surface texture is no longer required for rendering: instead a new texture of arbitrary resolution is synthesized at runtime. In addition to the compact procedural model we store elevation data, anyway required for the terrain rendering, and low-resolution geographic data. We show results of our method applied to a comparatively little cultivated region in Central Asia

Interactive Generation of Time-Evolving Snow-Covered Landscaped with Avalanches

We introduce a novel method for interactive generation of visually consistent, snow-covered landscapes and provide control of their dynamic evolution over time. Our main contribution is the real-time phenomenological simulation of avalanches and other user-guided events, such as tracks left by Nordic skiing, which can be applied to interactively sculpt the landscape. The terrain is modeled as a height field with additional layers for stable, compacted, unstable, and powdery snow, which behave in combination as a semi-viscous fluid. We incorporate the impact of several phenomena, including sunlight, temperature, prevailing wind direction, and skiing activities. The snow evolution includes snow-melt and snow-drift, which affect stability of the snow mass and the probability of avalanches. A user can shape landscapes and their evolution either with a variety of interactive brushes, or by prescribing events along a winter season time-line. Our optimized GPU-implementation allows interactive updates of snow type and depth across a large (10×10km) terrain, including real-time avalanches, making this suitable for visual assets in computer games. We evaluate our method through perceptual comparison against exiting methods and real snow-depth data

A Knowledge-based Approach for Creating Detailed Landscape Representations by Fusing GIS Data Collections with Associated Uncertainty

Geographic Information Systems (GIS) data for a region is of different types and collected from different sources, such as aerial digitized color imagery, elevation data consisting of terrain height at different points in that region, and feature data consisting of geometric information and properties about entities above/below the ground in that region. Merging GIS data and understanding the real world information present explicitly or implicitly in that data is a challenging task. This is often done manually by domain experts because of their superior capability to efficiently recognize patterns, combine, reason, and relate information. When a detailed digital representation of the region is to be created, domain experts are required to make best-guess decisions about each object. For example, a human would create representations of entities by collectively looking at the data layers, noting even elements that are not visible, like a covered overpass or underwater tunnel of a certain width and length. Such detailed representations are needed for use by processes like visualization or 3D modeling in applications used by military, simulation, earth sciences and gaming communities. Many of these applications are increasingly using digitally synthesized visuals and require detailed digital 3D representations to be generated quickly after acquiring the necessary initial data. Our main thesis, and a significant research contribution of this work, is that this task of creating detailed representations can be automated to a very large extent using a methodology which first fuses all Geographic Information System (GIS) data sources available into knowledge base (KB) assertions (instances) representing real world objects using a subprocess called GIS2KB. Then using reasoning, implicit information is inferred to define detailed 3D entity representations using a geometry definition engine called KB2Scene. Semantic Web is used as the semantic inferencing system and is extended with a data extraction framework. This framework enables the extraction of implicit property information using data and image analysis techniques. The data extraction framework supports extraction of spatial relationship values and attribution of uncertainties to inferred details. Uncertainty is recorded per property and used under Zadeh fuzzy semantics to compute a resulting uncertainty for inferred assertional axioms. This is achieved by another major contribution of our research, a unique extension of the KB ABox Realization service using KB explanation services. Previous semantics based research in this domain has concentrated more on improving represented details through the addition of artifacts like lights, signage, crosswalks, etc. Previous attempts regarding uncertainty in assertions use a modified reasoner expressivity and calculus. Our work differs in that separating formal knowledge from data processing allows fusion of different heterogeneous data sources which share the same context. Imprecision is modeled through uncertainty on assertions without defining a new expressivity as long as KB explanation services are available for the used expressivity. We also believe that in our use case, this simplifies uncertainty calculations. The uncertainties are then available for user-decision at output. We show that the process of creating 3D visuals from GIS data sources can be more automated, modular, verifiable, and the knowledge base instances available for other applications to use as part of a common knowledge base. We define our method’s components, discuss advantages and limitations, and show sample results for the transportation domain

Scalable Realtime Rendering and Interaction with Digital Surface Models of Landscapes and Cities

Interactive, realistic rendering of landscapes and cities differs substantially from classical terrain rendering. Due to the sheer size and detail of the data which need to be processed, realtime rendering (i.e. more than 25 images per second) is only feasible with level of detail (LOD) models. Even the design and implementation of efficient, automatic LOD generation is ambitious for such out-of-core datasets considering the large number of scales that are covered in a single view and the necessity to maintain screen-space accuracy for realistic representation. Moreover, users want to interact with the model based on semantic information which needs to be linked to the LOD model. In this thesis I present LOD schemes for the efficient rendering of 2.5d digital surface models (DSMs) and 3d point-clouds, a method for the automatic derivation of city models from raw DSMs, and an approach allowing semantic interaction with complex LOD models. The hierarchical LOD model for digital surface models is based on a quadtree of precomputed, simplified triangle mesh approximations. The rendering of the proposed model is proved to allow real-time rendering of very large and complex models with pixel-accurate details. Moreover, the necessary preprocessing is scalable and fast. For 3d point clouds, I introduce an LOD scheme based on an octree of hybrid plane-polygon representations. For each LOD, the algorithm detects planar regions in an adequately subsampled point cloud and models them as textured rectangles. The rendering of the resulting hybrid model is an order of magnitude faster than comparable point-based LOD schemes. To automatically derive a city model from a DSM, I propose a constrained mesh simplification. Apart from the geometric distance between simplified and original model, it evaluates constraints based on detected planar structures and their mutual topological relations. The resulting models are much less complex than the original DSM but still represent the characteristic building structures faithfully. Finally, I present a method to combine semantic information with complex geometric models. My approach links the semantic entities to the geometric entities on-the-fly via coarser proxy geometries which carry the semantic information. Thus, semantic information can be layered on top of complex LOD models without an explicit attribution step. All findings are supported by experimental results which demonstrate the practical applicability and efficiency of the methods

Appalachian Moderns: Poetry and Music, 1936-1947

Why has Appalachia been written out of the story of modernism? Current scholarship on American modernism’s geography proposes a bipartite model: proximal modernism in the North, a movement based in New York and Chicago concerning life in an urban zone, and distal modernism in the South, as a dispersed movement concerning life in an agrarian zone. Yet participating in another regional stream of modernism are Appalachians, a third group, whose homeland was defined neither by urbanism nor agrarianism, but was developed along a third developmental path: extractivism. This developmental model restructured state governments and laws to enlarge the region’s capacity to produce wood, minerals, coal, petroleum, and natural gas. Extractivism is thoroughly examined in works by Appalachians. This dissertation focuses on two such works, arguing that they reveal another, as yet overlooked, stream of modernism. Written on frontlines of industrial resource extraction, Gauley Mountain (1939) by West Virginian poet Louise McNeill and Folk Songs of the Hills (1947) by Kentucky musician Merle Travis make modernist interventions in form and content yet have never been classed as modernist, mostly going unnoticed by literary scholars. To better understand why this the case, I compare each of these two critically neglected figures with a historical contemporary who, at one point or another, did become established as a canonical modernist: Travis, with the undisputed “master of modernism” Louis Armstrong (1901-1971), a New Orleans musician sixteen years older than Travis but facing a similar turning point in style with his Town Hall Concert (1947); McNeill, with New York City poet Muriel Rukeyser (1913-1980), writer of The Book of the Dead (1938), who has been venerated in recent decades as a significant twentieth-century American writer. Close readings of these works, and their critical fates, reveal the geographic and regional indexing of cultural value in modernist studies. Specifically, uneven economic development positioned Appalachia within the cultural spheres of thirties poetry and forties music in a certain way, as a source not only of natural resources, but of cultural resources as well. Appalachian Moderns therefore works to widen our appreciation of American modernism’s geographic and historical dynamics

Geospecific Rendering of Alpine Terrain

. Realistic rendering of outdoor terrain requires both that the geometry of the environment be modeled accurately and that appropriate texturing by laid down on top of that geometry. While elevation data is widely available for much of the world and many methods exist for converting this data to forms suitable for graphics systems, we have much less experience with patterning the resulting surface. This paper describes an approach for using panchromatic aerial imagery to produce color views of alpine scenes. The method is able to remove shading and shadowing effects in the original image so that shading and shadowing appropriate to variable times of day can be added. Seasonal snow cover can be added in a physically plausible manner. Finally, 3--D instancing of trees and brush can be added in locations consistent with the imagery, significantly improving the visual quality. 1 Introduction Sophisticated techniques exist for converting real-world elevation data into a terrain..

Geospecific rendering of alpine terrain

Abstract. Realistic rendering of outdoor terrain requires both that the geometry of the environment be modeled accurately and that appropriate texturing by laid down on top of that geometry. While elevation data is widely available for much of the world and many methods exist for converting this data to forms suitable for graphics systems, we have much less experience with patterning the resulting surface. This paper describes an approach for using panchromatic aerial imagery to produce color views of alpine scenes. The method is able to remove shading and shadowing effects in the original image so that shading and shadowing appropriate to variable times of day can be added. Seasonal snow cover can be added in a physically plausible manner. Finally, 3–D instancing of trees and brush can be added in locations consistent with the imagery, significantly improving the visual quality.