Charles Otto

1.9k total citations · 1 hit paper
10 papers, 1.1k citations indexed

About

Charles Otto is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Experimental and Cognitive Psychology. According to data from OpenAlex, Charles Otto has authored 10 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 6 papers in Signal Processing and 1 paper in Experimental and Cognitive Psychology. Recurrent topics in Charles Otto's work include Face recognition and analysis (10 papers), Face and Expression Recognition (9 papers) and Biometric Identification and Security (6 papers). Charles Otto is often cited by papers focused on Face recognition and analysis (10 papers), Face and Expression Recognition (9 papers) and Biometric Identification and Security (6 papers). Charles Otto collaborates with scholars based in United States and India. Charles Otto's co-authors include Anil K. Jain, Hu Han, D. Wang, Xiaoming Liu, James A. Duncan, Nathan D. Kalka, Janet Anderson, Tim Miller, Patrick Grother and Brendan Klare and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Information Forensics and Security.

In The Last Decade

Charles Otto

10 papers receiving 1.0k citations

Hit Papers

IARPA Janus Benchmark - C: Face Dataset and Protocol 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Charles Otto United States 7 958 467 157 36 33 10 1.1k
Guowang Mu United States 11 1.1k 1.1× 324 0.7× 108 0.7× 18 0.5× 58 1.8× 15 1.1k
Luuk Spreeuwers Netherlands 17 696 0.7× 396 0.8× 94 0.6× 40 1.1× 45 1.4× 99 973
Cunjian Chen United States 14 521 0.5× 282 0.6× 64 0.4× 53 1.5× 30 0.9× 34 633
Shaoxin Li China 9 554 0.6× 234 0.5× 164 1.0× 34 0.9× 12 0.4× 19 687
Samarth Bharadwaj India 15 784 0.8× 708 1.5× 100 0.6× 158 4.4× 13 0.4× 27 979
Himanshu S. Bhatt India 14 523 0.5× 418 0.9× 95 0.6× 91 2.5× 9 0.3× 27 669
David S. Bolme United States 12 495 0.5× 250 0.5× 51 0.3× 39 1.1× 24 0.7× 25 591
Elham Tabassi United States 9 464 0.5× 446 1.0× 84 0.5× 109 3.0× 14 0.4× 27 677
Lacey Best-Rowden United States 10 374 0.4× 284 0.6× 26 0.2× 72 2.0× 11 0.3× 11 500
Insaf Adjabi Algeria 5 301 0.3× 145 0.3× 55 0.4× 44 1.2× 25 0.8× 8 449

Countries citing papers authored by Charles Otto

Since Specialization
Citations

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

Fields of papers citing papers by Charles Otto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Charles Otto

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

All Works

10 of 10 papers shown
1.
Kalka, Nathan D., James A. Duncan, Jeremy Dawson, & Charles Otto. (2019). IARPA Janus Benchmark Multi-Domain Face. 1–9. 4 indexed citations
2.
Anderson, Janet, et al.. (2019). Understanding Confounding Factors in Face Detection and Recognition. 1–8. 2 indexed citations
3.
Duncan, James A., Nathan D. Kalka, Tim Miller, et al.. (2018). IARPA Janus Benchmark - C: Face Dataset and Protocol. 158–165. 364 indexed citations breakdown →
4.
Otto, Charles, D. Wang, & Anil K. Jain. (2017). Clustering Millions of Faces by Identity. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(2). 289–303. 100 indexed citations
5.
Wang, D., Charles Otto, & Anil K. Jain. (2016). Face Search at Scale. IEEE Transactions on Pattern Analysis and Machine Intelligence. 39(6). 1122–1136. 77 indexed citations
6.
Otto, Charles, Brendan Klare, & Anil K. Jain. (2015). An efficient approach for clustering face images. 243–250. 6 indexed citations
8.
Best-Rowden, Lacey, Hu Han, Charles Otto, Brendan Klare, & Anil K. Jain. (2014). Unconstrained Face Recognition: Identifying a Person of Interest From a Media Collection. IEEE Transactions on Information Forensics and Security. 9(12). 2144–2157. 123 indexed citations
9.
Han, Hu, Charles Otto, Xiaoming Liu, & Anil K. Jain. (2014). Demographic Estimation from Face Images: Human vs. Machine Performance. IEEE Transactions on Pattern Analysis and Machine Intelligence. 37(6). 1148–1161. 227 indexed citations
10.
Han, Hu, Charles Otto, & Anil K. Jain. (2013). Age estimation from face images: Human vs. machine performance. 1–8. 157 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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