Michael Calonder

5.4k total citations · 2 hit papers
8 papers, 1.2k citations indexed

About

Michael Calonder is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, Michael Calonder has authored 8 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 7 papers in Aerospace Engineering and 2 papers in Artificial Intelligence. Recurrent topics in Michael Calonder's work include Robotics and Sensor-Based Localization (7 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Image Retrieval and Classification Techniques (1 paper). Michael Calonder is often cited by papers focused on Robotics and Sensor-Based Localization (7 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Image Retrieval and Classification Techniques (1 paper). Michael Calonder collaborates with scholars based in Switzerland, United States and France. Michael Calonder's co-authors include Pascal Fua, Vincent Lepetit, Mustafa Özuysal, Christoph Strecha, T. P. Trzcinski, Patrick Mihelich and Kurt Konolige and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, The International Journal of Robotics Research and Infoscience (Ecole Polytechnique Fédérale de Lausanne).

In The Last Decade

Michael Calonder

8 papers receiving 1.2k citations

Hit Papers

BRIEF: Computing a Local Binary Descriptor Very Fast 2009 2026 2014 2020 2011 2009 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Calonder Switzerland 6 1.1k 707 99 88 86 8 1.2k
Sareh Shirazi Australia 7 830 0.8× 569 0.8× 186 1.9× 70 0.8× 77 0.9× 15 907
Yakup Genç United States 16 965 0.9× 457 0.6× 51 0.5× 136 1.5× 65 0.8× 77 1.2k
Cédric Demonceaux France 20 1.0k 0.9× 715 1.0× 123 1.2× 136 1.5× 84 1.0× 89 1.3k
Christopher Geyer United States 16 963 0.9× 530 0.7× 69 0.7× 180 2.0× 60 0.7× 25 1.1k
Petr Gronát France 4 1.1k 1.0× 738 1.0× 177 1.8× 82 0.9× 207 2.4× 5 1.3k
Wen-Yan Lin Singapore 12 2.0k 1.9× 728 1.0× 63 0.6× 155 1.8× 218 2.5× 22 2.2k
Jean‐Charles Bazin South Korea 21 1.1k 1.0× 573 0.8× 99 1.0× 187 2.1× 111 1.3× 69 1.5k
Manuel Werlberger Austria 7 938 0.9× 703 1.0× 142 1.4× 60 0.7× 46 0.5× 7 1.1k
Daniel Ponsa Spain 13 809 0.7× 321 0.5× 49 0.5× 72 0.8× 197 2.3× 32 976
Enrique Dunn United States 15 734 0.7× 481 0.7× 49 0.5× 51 0.6× 44 0.5× 40 860

Countries citing papers authored by Michael Calonder

Since Specialization
Citations

This map shows the geographic impact of Michael Calonder'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 Michael Calonder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Calonder more than expected).

Fields of papers citing papers by Michael Calonder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Calonder. 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 Michael Calonder. The network helps show where Michael Calonder may publish in the future.

Co-authorship network of co-authors of Michael Calonder

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Calonder. A scholar is included among the top collaborators of Michael Calonder 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 Michael Calonder. Michael Calonder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Calonder, Michael, Vincent Lepetit, Mustafa Özuysal, et al.. (2011). BRIEF: Computing a Local Binary Descriptor Very Fast. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(7). 1281–1298. 569 indexed citations breakdown →
2.
Calonder, Michael. (2010). Robust, High-Speed Interest Point Matching for Real-Time Applications. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 5 indexed citations
3.
Konolige, Kurt, et al.. (2010). View-based Maps. The International Journal of Robotics Research. 29(8). 941–957. 176 indexed citations
4.
Calonder, Michael, Vincent Lepetit, & Pascal Fua. (2010). Pareto-optimal dictionaries for signatures. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 3011–3018. 1 indexed citations
5.
Özuysal, Mustafa, Michael Calonder, Vincent Lepetit, & Pascal Fua. (2009). Fast Keypoint Recognition Using Random Ferns. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32(3). 448–461. 404 indexed citations breakdown →
6.
Konolige, Kurt, et al.. (2009). View-based maps. 28 indexed citations
7.
Calonder, Michael, et al.. (2009). Compact signatures for high-speed interest point description and matching. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 357–364. 37 indexed citations
8.
Calonder, Michael. (2006). EKF SLAM vs. FastSLAM -- A comparison. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 4 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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