Publications | Conferences


Refereed Articles

J. Morel, A. Bac, C. Véga: Digital terrain model reconstruction from terrestrial LiDAR data using compactly supported radial basis, IEEE Computer Graphics and applications, 2017 (pdf).

dtm_plot_r1-e1502166808535.pngThis paper introduces a surface approximation algorithm dedicated to extracting digital terrain models from terrestrial laser scanning data acquired in forest areas. The method combines simultaneously terrain model reconstruction and hole filling. It is based on the combination of a quadtree subdivision of space guided by the local density and distribution of data together with a modeling of terrain model via radial basis functions used as partitions of unity for merging local quadratic approximations.


J. Morel: An Android Application to visualize point clouds and meshes in VR, Proceedings of the 11th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing, 2017 (pdf).


This paper presents a review of well-known rendering techniques and their adaptation to the features of OpenGL ES 2.0 to develop an Android application dedicated to the visualization of surface meshes and point clouds in virtual reality. Using the headtracking sensors of the smartphone, a generic Bluetooth controller and a virtual reality headset, this application has proven to be a powerful tool to investigate and explore 3D point clouds and meshed surfaces as a VR environment.


J. Morel, A. Bac, C. Véga: Computation of tree volume from terrestrial LiDAR data. Proceedings of the 9th Symposium on Mobile Mapping Technology, MMT 2015, UNSW, Sydney, Australia, 2015.

meshThis paper introduces an original methodological framework to compute an implicit surface of tree woody structure. Relying on the robustness of quantitative structure models to describe a rough tree structure, we replace the cylinders of those models by quadratic local approximations further merged by partition of unity. In doing so, we refine the tree shape reconstruction where data samples are available and preserve the supporting geometrical shape in the occlusions.





Surface Reconstruction Based on Forest Terrestrial LiDAR Data, February 2017 (pdf).

French Institute of Pondicherry, UMIFRE 21 CNRS-MAE, Pondicherry, India.

Laboratoire des Sciences de l’Information et des Systèmes, UMR 7296, Aix Marseille University, France.


Other Publications

J.Morel, A. Bac, C. Véga: Computation of tree volume from TLS data. Proceedings of Silvilaser, Geospatial Week, La Grande Motte, France, 2015

J. Morel, A. Bac, C. Véga: Forest carbon assessment from LiDAR 3D point cloud analysis. Regional Forum on Climate Change, 2015,AIT, Bangkok, Thailand, 2015

C. Véga, U. Vepakomma, J. Morel, J. L. Bader, G. Rajashekar, C. S. Jha, J. Ferêt, C. Proisy, R. Pélissier, V. K. Dadhwal: Aboveground biomass estimation of a complex tropical forest in India using LiDAR, Remote Sensing, 2015

V. Bonhomme, M. Castets, J. Morel, C. Gaucherel: Introducing the vectorial Kappa: An index to quantify congruence between vectorial mosaics, Ecological Indicators, 2015

C. Véga, A. Hamrouni, S. El Mokhtari, J. Morel, J. Bock, J.-P. Renaud, M. Bouvier, S. Durrieu: PTrees: A point-based approach to forest tree extraction from lidar data, International Journal of Applied Earth Observation and Geoinformation, 2014

C. Véga, S. Durrieu, J. Morel, T. Allouis: A sequential iterative dual-filter for Lidar terrain modeling optimized for complex forested environments, Computers & Geosciences, 2012