This workshop is developed in conjunction with ISPRS WGs III/4 and II/2. Many researchers have studied automated 3D reconstruction of objects and several workshops have been organized on this topic already. This workshop therefore has the multiple aims:
- to specify the minimum 3D modeling requirements of NMAs;
- to identify, together with industry and researches, the most efficient 3D object capture methodologies for very large areas (e.g. national coverage);
- recognizing that “as automated as possible” might not always be the most efficient solution (i.e. guaranteeing a valid 3D object output for 60% of the objects could be preferable over a solution that targets a higher percentage but requires higher levels of human verification);
- to examine in addition to the reconstruction processes, the issues of validation of generated objects;
- to examine the ability to remain consistent with the original source;
- to focus on the most prominent features in (the majority of) 3D topological models, buildings and transportation networks (including tunnels and bridges);
- to focus on 3D object generation including the generation of accuracy information on the generated data. Data capture methodologies that can be varied in their sources (e.g. LiDAR, aerial photogrammetry, terrestrial laser scanning, existing 2D data) are of interest but not the prime focus of the workshop;
- to explicitly address the distinction between initial data capture and the incremental update of existing national models, which will require embedding the 3D modeling within established processes of continuous incremental updating of countrywide data sets.
Please register via: http://3dsig.eventbrite.co.uk
Call for abstracts
To participate in this workshop, you are invited to give a presentation or demonstration on one of the above-mentioned topics. 300-500 words abstract can be sent to j.e.stoter [at] tudelft.nl, by 12 noon, 30th of September 2014
The abstracts will be used to organize the programme. Improved versions or full papers will not be requested.