IEEE Computer Graphics and Applications
Planning for complete sensor coverage in inspection
Computer Vision and Image Understanding
Viewpoint Selection using Viewpoint Entropy
VMV '01 Proceedings of the Vision Modeling and Visualization Conference 2001
Automated Texture Mapping of 3D City Models With Oblique Aerial Imagery
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
Legible Cities: Focus-Dependent Multi-Resolution Visualization of Urban Relationships
IEEE Transactions on Visualization and Computer Graphics
Finding paths through the world's photos
ACM SIGGRAPH 2008 papers
Modeling the World from Internet Photo Collections
International Journal of Computer Vision
A unified information-theoretic framework for viewpoint selection and mesh saliency
ACM Transactions on Applied Perception (TAP)
Efficient viewpoint assignment for urban texture documentation
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Information Theory Tools for Computer Graphics
Information Theory Tools for Computer Graphics
A next-best-view system for autonomous 3-D object reconstruction
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Photorealistic 3D models are used for visualization, interpretation and spatial measurement in many disciplines, such as cultural heritage, archaeology and geoscience. Using modern image- and laser-based 3D modelling techniques, it is normal to acquire more data than is finally used for 3D model texturing, as images may be acquired from multiple positions, with large overlap, or with different cameras and lenses. Such redundant image sets require sorting to restrict the number of images, increasing the processing efficiency and realism of models. However, selection of image subsets optimized for texturing purposes is an example of complex spatial analysis. Manual selection may be challenging and time-consuming, especially for models of rugose topography, where the user must account for occlusions and ensure coverage of all relevant model triangles. To address this, this paper presents a framework for computer-aided image geometry analysis and subset selection for optimizing texture quality in photorealistic models. The framework was created to offer algorithms for candidate image subset selection, whilst supporting refinement of subsets in an intuitive and visual manner. Automatic image sorting was implemented using algorithms originating in computer science and information theory, and variants of these were compared using multiple 3D models and covering image sets, collected for geological applications. The image subsets provided by the automatic procedures were compared to manually selected sets and their suitability for 3D model texturing was assessed. Results indicate that the automatic sorting algorithms are a promising alternative to manual methods. An algorithm based on a greedy solution to the weighted set-cover problem provided image sets closest to the quality and size of the manually selected sets. The improved automation and more reliable quality indicators make the photorealistic model creation workflow more accessible for application experts, increasing the user's confidence in the final textured model completeness.