Modeling and Acquisitions

Perspectives

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 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 user intervention throughout the 3D acquisition pipeline. Despite the significant advances regarding the automation of the algorithms, user interaction is still often required to fit parameters or to perform corrections. 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 and local 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 integrated methods built on the analysis of these different kinds of data, making it possible to capture the main features of the scanned objects, that will then be used to localize and guide the reconstruction process with minimum user interaction.

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3D model representation for real-time visualization

The huge size and complexity of models represented using standard triangle mesh data-structures involve numerous storage and visualization issues. Our research includes development of alternative representations offering both compactness and suitability for real-time realistic rendering, as well as suitability for some edition operations (virtual sculpture, simulation of natural phenomena).

Representations based on the displacement mapping technique and hierarchical voxel grids efficiently take advantage of the computational power of current graphic processors. These data-structures both require large storage space in graphic memory for complex 3D models, that is not necessarily justified by the local geometry. In order to visualize complex models with limited memory resources, we are developing a new approach of procedural modeling for surfaces based on displacement maps and procedural generation techniques.