Modeling and Acquisitions

Representation of 3D scanned objects for real-time visualization

3D model reconstruction from multiple data sources

We have designed an efficient 3D acquisition pipeline for constructing 3D geometric models from scanned objects, that reproduce both the shape and appearance of the objects at different levels of detail. Unfortunately, these techniques do not easily scale to hundreds of millions or billions of sample points. This is first due to the complexity of the algorithms and/or their memory consumption. Out-of-core and streaming techniques that operate on data-structures that are stored in mass storage memory are only suitable for localized treatments or processing at low scale, at the expense of a reduced robustness to defect-laden data incorporating noise or missing parts.

Another factor that hampers scalability is the frequency of the manual interventions throughout the processing pipeline. Despite the significant advances regarding the automation of the algorithms, user interaction is still much required to fit parameters or to perform corrections is still high in many cases. Sometimes it is required to restart the whole process from scratch, which is very penalizing when performing complex operations on large data sets. A major difficulty in reconstructing geometric models is the lack of prior information about the properties of the scanned objects: structure, global shape, components, etc. Only 3D-scanned data are generally taken into account by existing reconstruction algorithms at this step of the pipeline.

To overcome these issues, we aim at developing new techniques taking advantage of the complementarity of multiple data sources for the reconstruction of geometric models: scans, photographs, 3D models with similar shape and/or appearance, sketches, etc. Our goal is to devise methods built on the analysis of these different kinds of data, making it possible to capture the important features of the scanned objects, that will be then used to localize and guide the reconstruction process with minimum user interaction.