Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.

Cologne, Germany, Building Zones, 1905 (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Uebersichtsplan zur Banordnung für den Stadtkreis Cöln. It was published by Wilh. Gross in 1905. Scale 1:15,000. Covers Cologne, Germany. Map in German. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Deutsches Hauptdreiecksnetz (DHDN) 3-degree Gauss-Kruger Zone 2 coordinate system. All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, index maps, legends, or other information associated with the principal map. This map shows features such as roads, railroads, drainage, building zones, built-up areas and selected buildings, fortification, and more. Includes legend of zones. This layer is part of a selection of digitally scanned and georeferenced historic maps from The Harvard Map Collection as part of the Imaging the Urban Environment project. Maps selected for this project represent major urban areas and cities of the world, at various time periods. These maps typically portray both natural and manmade features at a large scale. The selection represents a range of regions, originators, ground condition dates, scales, and purposes.

Posterior Probability Modeling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands

The application of custom classification techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological field survey is presented in this paper. Research is focused on the identification of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classifier based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identified through geological field survey. Testing shows the prospective ability of this technique and significance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classifiers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efficacy model is generated showing the utility of such approaches to archaeological field survey.

West elevation, Neville Bonner Building, Brisbane

Riverside Expressway building, Expressway on right.

West elevation, Neville Bonner Building, Brisbane

William St building, facing Riverside Expressway. Landscaped courtyard space in foreground.

West elevation, Neville Bonner Building, Brisbane

William St building, facing Riverside Expressway.

Sunshading fins, Neville Bonner Building, Brisbane

Steel shading structure to East elevation of Riverside Expressway building. William St building and main entry area in background.

Windows, Neville Bonner Building, Brisbane

North elevation, Riverside Expressway building.

Facade articulation, Neville Bonner Building, Brisbane

Detail of precast concrete sunshading panels to freeway (West) elevation.

South elevation, Neville Bonner Building, Brisbane

William St building, as seen from across Riverside Expressway off-ramp.

Main entry, William St, Neville Bonner Building, Brisbane

William St building-Riverside Expressway building junction.

Facade articulation, Neville Bonner Building, Brisbane

Detail of precast concrete sunshading panels to freeway (West) elevation.

North elevation, Neville Bonner Building, Brisbane

As seen from Queens Wharf Road.

Entrance, Agriculture and Entomology Building, Brisbane

View to entrance.