Geometric Modeling, Simulation and Interaction Assessment2016-2021

Objectives and challenges

The work of the "Geometric Modeling, Simulation and Interaction" theme aims to tackle two major issues. The first concerns the development of tools for the geometric and topological modelling and analysis of 3D objects, both generic and robust enough to be adapted to concrete cases. The second relates to human-machine interaction in a virtual environment, taking into account both human perception of this environment and human-to-machine communication.

Participants

• Three full professors: Dominique Bechmann, David Cazier and Franck Hétroy-Wheeler
• One senior researcher: Birgitta Dresp-Langley (2019-2020)
• Gutenberg Chair 2019, Daniel Oberfeld-Twistel, Associate Professor at Johannes Gutenberg - Universität Mainz (Institute of Psychology)
• Three associate professors: Antonio Capobianco, Jérôme Grosjean and Pierre Kraemer
• Three research engineers: Thierry Blandet, Sylvain Thery and Joris Ravaglia (since 10/2020)
• One engineer from the GEOSIRIS company since 01/09/2018, Lionel Untereiner (research engineer associated with the team since 8/06/2020)
• Postdoctoral students: Sabah Boustila (from 15/01/2020 to 31/12/2020), Flavien Lecuyer (teaching associate IUT Haguenau 2020-2021), Joris Ravaglia (Unistra Idex 2018 - Attractivity programme from 10/2019 to 09/2020)
• PhD students: Paul Viville (Unistra doctoral contract from 10/2019 to 09/2022), Quentin Wendling (Unistra doctoral contract from 10/2019 to 09/2022), Julien Casarin (CIFRE grant with Gfi-Labs from 2016 to 2019. Defended the 30th of September 2019), Alexandre Hurstel (Contract through the 3D-Surg project from 2015 to 2019. Defended the 30th of September 2019), Sabah Boustila (Contract through the CIMBEES project from 2012 to 2015. Defended the 25th of May 2016), Mélinda Boukhana (CIFRE grant with Arvalis from 03/2018 to 12/2021. Defended the 15th of December 2021), Katia Mirande (Contract through the ROMI project from 11/2018 to 04/2022).

Results

Construction of a connection surface for a 7-way junction (left). Pairing of hexahedra around a 3-way junction (right).

Examples of hexahedral meshes obtained with our method.

Hexahedral Mesh Generation

The construction of a volumetric mesh for a given geometric domain is a complex problem that has been tackled for many years. The generation of purely hexahedral meshes for domains of any shape is still an open problem. We have developed a processing chain for the generation of hexahedral meshes for domains whose shape can be represented by their skeleton. By exploiting this representation, the generated mesh is well aligned with the geometry of the domain and its connectivity is as regular as possible. The main difficulty lies in the processing of the connectivity of the mesh at the level of the branches of the skeleton which can have any number of incident branches. We have proposed a new solution with the construction of connection surfaces that encode the connectivity of the final solid mesh around each of the vertices of the skeleton. Each vertex is processed independently by choosing, according to the local configuration, an appropriate method. Since these methods are mutually compatible, no system with global constraints needs to be solved. In the end, the proposed processing chain makes it possible to manage complex shapes even in the presence of cycles and many steps can process the cells in parallel. Compared to the state of the art, the quality of the meshes obtained is at least similar if not better. The implemented algorithm is robust to the presence of cycles and generates more symmetric and regular results in many cases. [7-VKB20] [4-VKB21]

Analysis of Plant 3D Point Clouds

Comparison of six surface reconstruction methods on an oak leaf point cloud acquired by laser scanning.

In fundamental as well as applied biology, the accurate measurement of geometric features of plants and trees (height, angles of insertion of branches, lengths between nodes, areas of leaves, etc.) is necessary to understand the interaction of a plant with its environment (phenotyping) or the mechanisms underlying its growth, as well as to validate structure-function models (FSPM). In recent years, the development of passive (photogrammetry) or active (laser scanners) acquisition systems has made it possible to limit manual measurements which are costly and require cutting and therefore destroying the plants. These systems generate a virtual model of the object under study in the form of a three-dimensional point cloud. Such a cloud of points must then undergo various geometric treatments: denoising, decomposition into botanical organs (stem or trunk, branches, petioles, leaves), reconstruction of a surface model for each organ, temporal tracking, etc.

Our contribution to such a processing chain is threefold. We propose a method for the robust segmentation of a plant point cloud into botanical organs, based on both a spectral analysis of the point cloud and the incorporation of botanical knowledge (PhD thesis of Katia Mirande, 2018-2022, [7-MHG20]). A spectral analysis makes it possible to determine very precisely the boundaries between organs, in particular between the petiole and the blade of a leaf. The use of prior knowledge on the structure of the plant in a probabilistic algorithm globally improves the robustness of the segmentation. Our second contribution concerns the reconstruction of the surface of a limb, with the aim of precisely estimating its area (PhD thesis of Mélinda Boukhana, 2018-2021, [7-BRHL20]). In particular, we conducted a comparative study between seven classical methods for surface reconstruction, according to nine criteria that we defined for the occasion and using an original synthetic model of a 3D point cloud of a leaf blade. We show that none of these methods robustly estimate the area of ​​a limb, and we propose a more efficient alternative approach based on a Bézier surface. Finally, we propose a multi-scale algorithm for point-to-point monitoring of 3D point clouds of growing plants (Haolin Pan's Master thesis, [4- PHCC21]). Our algorithm is based on the computation of a topological skeleton of the plant. This work was carried out in collaboration with plant specialists, respectively C. Godin (Inria Lyon), B. de Solan (Arvalis) and D. Colliaux (Sony Computer Science Laboratory).