Jacques‐Olivier Lachaud

1.5k total citations
48 papers, 483 citations indexed

About

Jacques‐Olivier Lachaud is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Jacques‐Olivier Lachaud has authored 48 papers receiving a total of 483 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Computer Vision and Pattern Recognition, 19 papers in Computational Mechanics and 16 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Jacques‐Olivier Lachaud's work include Digital Image Processing Techniques (34 papers), Medical Image Segmentation Techniques (22 papers) and 3D Shape Modeling and Analysis (16 papers). Jacques‐Olivier Lachaud is often cited by papers focused on Digital Image Processing Techniques (34 papers), Medical Image Segmentation Techniques (22 papers) and 3D Shape Modeling and Analysis (16 papers). Jacques‐Olivier Lachaud collaborates with scholars based in France, United States and Canada. Jacques‐Olivier Lachaud's co-authors include Annick Montanvert, David Cœurjolly, Dominique Attali, Bertrand Kerautret, Boris Thibert, Benjamin Taton, Srečko Brlek, Fabien Feschet, Christophe Reutenauer and Édouard Oudet and has published in prestigious journals such as Pattern Recognition, Pattern Recognition Letters and Medical Image Analysis.

In The Last Decade

Jacques‐Olivier Lachaud

44 papers receiving 459 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jacques‐Olivier Lachaud France 13 343 181 163 60 37 48 483
Mohamed S. Ebeida United States 12 144 0.4× 202 1.1× 276 1.7× 46 0.8× 22 0.6× 33 413
Mona Mahmoudi United States 4 507 1.5× 249 1.4× 67 0.4× 15 0.3× 42 1.1× 6 622
Pablo Arias France 11 427 1.2× 73 0.4× 56 0.3× 16 0.3× 16 0.4× 34 507
Paul Burchard United States 5 163 0.5× 244 1.3× 184 1.1× 16 0.3× 23 0.6× 5 392
Yves Willems Belgium 10 412 1.2× 153 0.8× 451 2.8× 9 0.1× 10 0.3× 25 575
Andrés Solé Spain 6 434 1.3× 175 1.0× 26 0.2× 52 0.9× 10 0.3× 10 544
Ka Chun Lam Hong Kong 8 160 0.5× 167 0.9× 100 0.6× 21 0.3× 34 0.9× 22 328
Ehud Artzy United States 7 216 0.6× 91 0.5× 152 0.9× 35 0.6× 10 0.3× 8 337
Erik Brisson United States 7 138 0.4× 172 1.0× 223 1.4× 32 0.5× 19 0.5× 12 412

Countries citing papers authored by Jacques‐Olivier Lachaud

Since Specialization
Citations

This map shows the geographic impact of Jacques‐Olivier Lachaud's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jacques‐Olivier Lachaud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacques‐Olivier Lachaud more than expected).

Fields of papers citing papers by Jacques‐Olivier Lachaud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacques‐Olivier Lachaud. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jacques‐Olivier Lachaud. The network helps show where Jacques‐Olivier Lachaud may publish in the future.

Co-authorship network of co-authors of Jacques‐Olivier Lachaud

This figure shows the co-authorship network connecting the top 25 collaborators of Jacques‐Olivier Lachaud. A scholar is included among the top collaborators of Jacques‐Olivier Lachaud based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jacques‐Olivier Lachaud. Jacques‐Olivier Lachaud is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lachaud, Jacques‐Olivier, Pascal Romon, & Boris Thibert. (2022). Corrected Curvature Measures. Discrete & Computational Geometry. 68(2). 477–524. 1 indexed citations
2.
Cœurjolly, David, et al.. (2021). Digital Surface Regularization With Guarantees. IEEE Transactions on Visualization and Computer Graphics. 27(6). 2896–2907. 2 indexed citations
3.
Lachaud, Jacques‐Olivier, et al.. (2020). An Optimized Framework for Plane-Probing Algorithms. Journal of Mathematical Imaging and Vision. 62(5). 718–736. 2 indexed citations
4.
Lachaud, Jacques‐Olivier, et al.. (2020). An Elastica-Driven Digital Curve Evolution Model for Image Segmentation. Journal of Mathematical Imaging and Vision. 63(1). 1–17. 4 indexed citations
5.
Bonneel, Nicolas, et al.. (2018). Mumford‐Shah Mesh Processing using the Ambrosio‐Tortorelli Functional. Computer Graphics Forum. 37(7). 75–85. 9 indexed citations
6.
Lachaud, Jacques‐Olivier, et al.. (2015). An output-sensitive algorithm to compute the normal vector of a digital plane. Theoretical Computer Science. 624. 73–88. 4 indexed citations
7.
Lachaud, Jacques‐Olivier, et al.. (2015). Robust Geometry Estimation Using the Generalized Voronoi Covariance Measure. SIAM Journal on Imaging Sciences. 8(2). 1293–1314. 10 indexed citations
8.
Kerautret, Bertrand & Jacques‐Olivier Lachaud. (2014). Meaningful Scales Detection: an Unsupervised Noise Detection Algorithm for Digital Contours. Image Processing On Line. 4. 98–115. 2 indexed citations
9.
Lachaud, Jacques‐Olivier, et al.. (2012). Two efficient algorithms for computing the characteristics of a subsegment of a digital straight line. Discrete Applied Mathematics. 161(15). 2293–2315. 2 indexed citations
10.
Lachaud, Jacques‐Olivier, et al.. (2011). Two linear-time algorithms for computing the minimum length polygon of a digital contour. Discrete Applied Mathematics. 159(18). 2229–2250. 5 indexed citations
11.
Bretin, Élie, Jacques‐Olivier Lachaud, & Édouard Oudet. (2011). Regularization of Discrete Contour by Willmore Energy. Journal of Mathematical Imaging and Vision. 40(2). 214–229. 12 indexed citations
12.
Lachaud, Jacques‐Olivier, et al.. (2008). Equivalence between Closed Connected n-G-Maps without Multi-Incidence and n-Surfaces. Journal of Mathematical Imaging and Vision. 32(1). 1–22. 1 indexed citations
13.
Lachaud, Jacques‐Olivier, et al.. (2007). Convex Digital Polygons, Maximal Digital Straight Segments and Convergence of Discrete Geometric Estimators. Journal of Mathematical Imaging and Vision. 27(2). 139–156. 12 indexed citations
14.
Lachaud, Jacques‐Olivier, et al.. (2006). Fast, accurate and convergent tangent estimation on digital contours. Image and Vision Computing. 25(10). 1572–1587. 28 indexed citations
15.
Lachaud, Jacques‐Olivier & Benjamin Taton. (2005). Deformable model with a complexity independent from image resolution. Computer Vision and Image Understanding. 99(3). 453–475. 19 indexed citations
16.
Lachaud, Jacques‐Olivier, et al.. (2005). Computation of homology groups and generators. Computers & Graphics. 30(1). 62–69. 13 indexed citations
17.
Lachaud, Jacques‐Olivier & Benjamin Taton. (2004). Resolution independent deformable model. Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.. 237–240 Vol.2. 1 indexed citations
18.
Attali, Dominique & Jacques‐Olivier Lachaud. (2001). Delaunay conforming iso-surface, skeleton extraction and noise removal. Computational Geometry. 19(2-3). 175–189. 29 indexed citations
19.
20.
Lachaud, Jacques‐Olivier & Annick Montanvert. (1999). Deformable meshes with automated topology changes for coarse-to-fine three-dimensional surface extraction. Medical Image Analysis. 3(2). 187–207. 80 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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