Florent Dupont

A new CAD mesh segmentation method, based on curvature tensor analysis

This paper presents a new and efficient algorithm for the decomposition of 3D arbitrary triangle meshes and particularly optimized triangulated CAD meshes. The algorithm is based on the curvature tensor field analysis and presents two distinct complementary steps: a region based segmentation, which is an improvement of that presented by Lavoue et al. [Lavoue G, Dupont F, Baskurt A. Constant curvature region decomposition of 3D-meshes by a mixed approach vertex-triangle, J WSCG 2004;12(2):245-52] and which decomposes the object into near constant curvature patches, and a boundary rectification based on curvature tensor directions, which corrects boundaries by suppressing their artefacts or discontinuities. Experiments conducted on various models including both CAD and natural objects, show satisfactory results. Resulting segmented patches, by virtue of their properties (homogeneous curvature, clean boundaries) are particularly adapted to computer graphics tasks like parametric or subdivision surface fitting in an adaptive compression objective.

Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals

[1] Satellite-passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resolution introduces uncertainties to SWE retrievals due to the surface heterogeneity within individual pixels. In this article, we investigate the coupling of a thermodynamic multilayered snow model with a passive microwave emission model. Results show that the snow model itself provides poor SWE simulations when compared to field measurements from two major field campaigns. Coupling the snow and microwave emission models with successive iterations to correct the influence of snow grain size and density significantly improves SWE simulations. This method was further validated using an additional independent data set, which also showed significant improvement using the two-step iteration method compared to standalone simulations with the snow model.

3D Mesh Compression: Survey, Comparisons, and Emerging Trends

3D meshes are commonly used to represent virtual surface and volumes. However, their raw data representations take a large amount of space. Hence, 3D mesh compression has been an active research topic since the mid 1990s. In 2005, two very good review articles describing the pioneering works were published. Yet, new technologies have emerged since then. In this article, we summarize the early works and put the focus on these novel approaches. We classify and describe the algorithms, evaluate their performance, and provide synthetic comparisons. We also outline the emerging trends for future research.

Streaming compressed 3D data on the web using JavaScript and WebGL

With the development of Web3D technologies, the delivery and visualization of 3D models on the web is now possible and is bound to increase both in the industry and for the general public. However the interactive remote visualization of 3D graphic data in a web browser remains a challenging issue. Indeed, most of existing systems suffer from latency (due to the data downloading time) and lack of adaptation to heterogeneous networks and client devices (i.e. the lack of levels of details); these drawbacks seriously affect the quality of user experience. This paper presents a technical solution for streaming and visualization of compressed 3D data on the web. Our approach leans upon three strong features: (1) a dedicated progressive compression algorithm for 3D graphic data with colors producing a binary compressed format which allows a progressive decompression with several levels of details; (2) the introduction of a JavaScript halfedge data structure allowing complex geometrical and topological operations on a 3D mesh; (3) the multi-thread JavaScript/WebGL implementation of the decompression scheme allowing 3D data streaming in a web browser. Experiments and comparison with existing solutions show promising results in terms of latency, adaptability and quality of user experience.

Improved Corrections of Forest Effects on Passive Microwave Satellite Remote Sensing of Snow Over Boreal and Subarctic Regions

Microwave radiometry has been extensively used in order to estimate snow water equivalent in northern regions. However, for boreal and taiga environments, the presence of forest causes important uncertainties in the estimates. Variations in snow cover and vegetation in northeastern Canada (north of the Québec province) were characterized in a transect from 50°N to 60 °N during the International Polar Year field campaign of February 2008. Forest properties show a strong latitudinal gradient in fraction and stem volume. A large database (>; 2000 points with a stem volume ranging between 0 and 700 m3 ·ha-1) showed that brightness temperatures (Tb) decrease as forest cover fraction decreases until a cover fraction of about 25% is reached. Furthermore, Tb values saturate at high stem volume, particularly at 37 GHz. We defined new relationships for the forest transmissivity as a function of stem volume and depending on the frequency/polarization. The proposed relationships give asymptotic transmissivity saturation levels of 0.51, 0.55, 0.53, and 0.53 for 19 GHz [vertical (V) polarization], 19 GHz [horizontal (H) polarization], 37 GHz (V polarization), and 37 GHz (H polarization), respectively. These relationships were used to estimate snow Tb from the Advanced Microwave Scanning Radiometer-Earth Observing System brightness temperatures at 18.7 and 36.5 GHz, and results show an estimated snow brightness temperature well correlated to the airborne snow brightness temperatures over vegetation-free areas.

Brightness Temperature Simulations of the Canadian Seasonal Snowpack Driven by Measurements of the Snow Specific Surface Area

Snow grain size is the snowpack parameter that most affects the microwave snow emission. The specific surface area (SSA) of snow is a metric that allows rapid and reproducible field measurements and that well represents the grain size. However, this metric cannot be used directly in microwave snow emission models (MSEMs). The aim of this paper is to evaluate the suitability and the adaptations required for using the SSA in two MSEMs, i.e., the Dense Media Radiative Theory-Multilayer model (DMRT-ML) and the Helsinki University of Technology model (HUT n-layer), based on in situ radiometric measurements. Measurements of the SSA, using snow reflectance in the short-wave infrared, were taken at 20 snowpits in various environments (e.g., grass, tundra, and dry fen). The results show that both models required a scaling factor for the SSA values to minimize the root-mean-square error between the measured and simulated brightness temperatures. For DMRT-ML, the need for a scaling factor is likely due to the oversimplified representation of snow as spheres of ice with a uniform radius. We hypothesize that the need for a scaling factor is related to the grain size distribution of snow and the stickiness between grains. For HUT n-layer, using the SSA underestimates the attenuation by snow, particularly for snowpacks with a significant amount of depth hoar. This paper provides a reliable description of the grain size for DMRT-ML, which is of particular interest for the assimilation of satellite passive microwave data in snow models.

Rate-distortion optimization for progressive compression of 3D mesh with color attributes

We propose a new lossless progressive compression algorithm based on rate-distortion optimization for meshes with color attributes; the quantization precision of both the geometry and the color information is adapted to each intermediate mesh during the encoding/decoding process. This quantization precision can either be optimally determined with the use of a mesh distortion measure or quasi-optimally decided based on an analysis of the mesh complexity in order to reduce the calculation time. Furthermore, we propose a new metric which estimates the geometry and color importance of each vertex during the simplification in order to faithfully preserve the feature elements. Experimental results show that our method outperforms the state-of-the-art algorithm for colored meshes and competes with the most efficient algorithms for non-colored meshes.

On digital plane preimage structure

In digital geometry, digital straightness is an important concept both for practical motivations and theoretical interests. Concerning the digital straightness in dimension 2, many digital straight line characterizations exist and the digital straight segment preimage is well known. In this article, we investigate the preimage associated to digital planes. More precisely, we present first structure theorems that describe the preimage of a digital plane. Furthermore, we present a bound on the number of preimage faces under some given hypotheses.

A new subdivision based approach for piecewise smooth approximation of 3D polygonal curves

This paper presents an algorithm dealing with the data reduction and the approximation of 3D polygonal curves. Our method is able to approximate efficiently a set of straight 3D segments or points with a piecewise smooth subdivision curve, in a near optimal way in terms of control point number. Our algorithm is a generalization for subdivision rules, including sharp vertex processing, of the Active B-Spline Curve developed by Pottmann et al. We have also developed a theoretically demonstrated approach, analysing curvature properties of B-Splines, which computes a near optimal evaluation of the initial number and positions of control points. Moreover, our original Active Footpoint Parameterization method prevents wrong matching problems occurring particularly for self-intersecting curves. Thus, the stability of the algorithm is highly increased. Our method was tested on different sets of curves and gives satisfying results regarding to approximation error, convergence speed and compression rate. This method is in line with a larger 3D CAD object compression scheme by piecewise subdivision surface approximation. The objective is to fit a subdivision surface on a target patch by first fitting its boundary with a subdivision curve whose control polygon will represent the boundary of the surface control polyhedron.

Contributing vertices-based Minkowski sum computation of convex polyhedra

Minkowski sum is an important operation. It is used in many domains such as: computer-aided design, robotics, spatial planning, mathematical morphology, and image processing. We propose a novel algorithm, named the Contributing Vertices-based Minkowski Sum (CVMS) algorithm for the computation of the Minkowski sum of convex polyhedra. The CVMS algorithm allows to easily obtain all the facets of the Minkowski sum polyhedron only by examining the contributing vertices-a concept we introduce in this work, for each input facet. We exploit the concept of contributing vertices to propose the Enhanced and Simplified Slope Diagram-based Minkowski Sum (ESSDMS) algorithm, a slope diagram-based Minkowski sum algorithm sharing some common points with the approach proposed by Wu et al. [Wu Y, Shah J, Davidson J. Improvements to algorithms for computing the Minkowski sum of 3-polytopes. Comput Aided Des. 2003; 35(13): 1181-92]. The ESSDMS algorithm does not embed input polyhedra on the unit sphere and does not need to perform stereographic projections. Moreover, the use of contributing vertices brings up more simplifications and improves the overall performance. The implementations for the mentioned algorithms are straightforward, use exact number types, produce exact results, and are based on CGAL, the Computational Geometry Algorithms Library. More examples and results of the CVMS algorithm for several convex polyhedra can be found at http://liris.cnrs.fr/hichem.barki/mksum/CVMS-convex.