Diego Macrini

786 total citations
12 papers, 463 citations indexed

About

Diego Macrini is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Signal Processing. According to data from OpenAlex, Diego Macrini has authored 12 papers receiving a total of 463 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 3 papers in Aerospace Engineering and 2 papers in Signal Processing. Recurrent topics in Diego Macrini's work include Advanced Image and Video Retrieval Techniques (8 papers), Graph Theory and Algorithms (5 papers) and Image Retrieval and Classification Techniques (3 papers). Diego Macrini is often cited by papers focused on Advanced Image and Video Retrieval Techniques (8 papers), Graph Theory and Algorithms (5 papers) and Image Retrieval and Classification Techniques (3 papers). Diego Macrini collaborates with scholars based in Canada, United States and Sweden. Diego Macrini's co-authors include Sven Dickinson, Kaleem Siddiqi, Ali Shokoufandeh, Sylvain Bouix, Juan Zhang, Steven W. Zucker, David J. Fleet, M. Fatih Demirci, Cristian Sminchisescu and Alexandru Telea and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Computer Vision and Image Understanding and Machine Vision and Applications.

In The Last Decade

Diego Macrini

12 papers receiving 442 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Diego Macrini Canada	10	396	185	58	49	46	12	463
Roee Litman Israel	11	473 1.2×	363 2.0×	103 1.8×	80 1.6×	61 1.3×	15	610
Ulrich Schlickewei Germany	4	336 0.8×	377 2.0×	130 2.2×	63 1.3×	23 0.5×	5	482
Yonathan Aflalo Israel	7	152 0.4×	121 0.7×	57 1.0×	15 0.3×	46 1.0×	11	242
Shangzhe Wu United Kingdom	8	326 0.8×	174 0.9×	103 1.8×	65 1.3×	17 0.4×	18	411
Thomas Schoenemann Germany	10	306 0.8×	62 0.3×	27 0.5×	41 0.8×	47 1.0×	18	386
Leonidas Guibas United States	7	253 0.6×	289 1.6×	155 2.7×	55 1.1×	13 0.3×	14	393
Laura Papaleo Italy	8	134 0.3×	59 0.3×	49 0.8×	29 0.6×	18 0.4×	24	244
J. Subrahmonia United States	9	365 0.9×	66 0.4×	16 0.3×	46 0.9×	137 3.0×	21	444
Adrien Poulenard United States	8	191 0.5×	207 1.1×	95 1.6×	36 0.7×	20 0.4×	10	340

Countries citing papers authored by Diego Macrini

Since Specialization

Citations

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

Fields of papers citing papers by Diego Macrini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diego Macrini

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

All Works

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12 of 12 papers shown

Macrini, Diego, et al.. (2014). The Current State and TRL Assessment of People Tracking Technology for Video Surveillance Applications. 2 indexed citations

Shokoufandeh, Ali, et al.. (2012). Many-to-many feature matching in object recognition: a review of three approaches. IET Computer Vision. 6(6). 500–513. 16 indexed citations

Macrini, Diego, Sven Dickinson, David J. Fleet, & Kaleem Siddiqi. (2011). Object categorization using bone graphs. Computer Vision and Image Understanding. 115(8). 1187–1206. 17 indexed citations

Macrini, Diego, Sven Dickinson, David J. Fleet, & Kaleem Siddiqi. (2011). Bone graphs: Medial shape parsing and abstraction. Computer Vision and Image Understanding. 115(7). 1044–1061. 23 indexed citations

Macrini, Diego, Kaleem Siddiqi, & Sven Dickinson. (2008). From skeletons to bone graphs: Medial abstraction for object recognition. 1–8. 42 indexed citations

Siddiqi, Kaleem, Juan Zhang, Diego Macrini, et al.. (2007). Retrieving articulated 3-D models using medial surfaces. Machine Vision and Applications. 19(4). 261–275. 182 indexed citations

Shokoufandeh, Ali, et al.. (2006). The representation and matching of categorical shape. Computer Vision and Image Understanding. 103(2). 139–154. 22 indexed citations

Eede, Matthijs van, et al.. (2006). Canonical Skeletons for Shape Matching. TU/e Research Portal. 64–69. 31 indexed citations

Qureshi, Faisal Z., et al.. (2005). A Computer Vision System for Spaceborne Safety Monitoring. 603. 119. 1 indexed citations

10.

Shokoufandeh, Ali, Diego Macrini, Sven Dickinson, Kaleem Siddiqi, & Steven W. Zucker. (2005). Indexing hierarchical structures using graph spectra. IEEE Transactions on Pattern Analysis and Machine Intelligence. 27(7). 1125–1140. 86 indexed citations

11.

Macrini, Diego, Ali Shokoufandeh, Sven Dickinson, Kaleem Siddiqi, & Steven W. Zucker. (2003). View-based 3-D object recognition using shock graphs. 3. 24–28. 30 indexed citations

12.

Macrini, Diego. (2003). Indexing and Matching for View-Based 3-D Object Recognition Using Shock Graphs. TSpace. 11 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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