Volker Eiselein

1.4k total citations · 1 hit paper
25 papers, 816 citations indexed

About

Volker Eiselein is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Volker Eiselein has authored 25 papers receiving a total of 816 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 4 papers in Signal Processing. Recurrent topics in Volker Eiselein's work include Video Surveillance and Tracking Methods (17 papers), Anomaly Detection Techniques and Applications (11 papers) and Human Pose and Action Recognition (8 papers). Volker Eiselein is often cited by papers focused on Video Surveillance and Tracking Methods (17 papers), Anomaly Detection Techniques and Applications (11 papers) and Human Pose and Action Recognition (8 papers). Volker Eiselein collaborates with scholars based in Germany, France and Italy. Volker Eiselein's co-authors include Thomas Sikora, Erik Bochinski, Tobias Senst, T. Sikora, Alexander Kühn, Daniel J. Arp, Jean‐Luc Dugelay, Hajer Fradi, Maik Simon and Antonio Penta and has published in prestigious journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Information Forensics and Security and Signal Processing Image Communication.

In The Last Decade

Volker Eiselein

25 papers receiving 779 citations

Hit Papers

High-Speed tracking-by-detection without using image info... 2017 2026 2020 2023 2017 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. High-Speed tracking-by-detection without using image information
    2017 430 citations Erik Bochinski, Volker Eiselein et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Volker Eiselein Germany 10 719 242 158 104 77 25 816
Erik Bochinski Germany 8 638 0.9× 170 0.7× 143 0.9× 99 1.0× 91 1.2× 15 774
Jiaolong Xu Spain 13 681 0.9× 210 0.9× 131 0.8× 172 1.7× 92 1.2× 26 887
Danda Pani Paudel Switzerland 16 742 1.0× 190 0.8× 289 1.8× 73 0.7× 34 0.4× 62 917
Stefan Munder Germany 5 888 1.2× 254 1.0× 106 0.7× 119 1.1× 202 2.6× 5 1000
Michael D. Breitenstein Switzerland 9 1.1k 1.5× 430 1.8× 181 1.1× 76 0.7× 75 1.0× 11 1.2k
David Duggins United States 6 874 1.2× 187 0.8× 161 1.0× 119 1.1× 80 1.0× 9 1.0k
Amir Sadeghian United States 6 462 0.6× 109 0.5× 125 0.8× 69 0.7× 90 1.2× 8 548
Kimin Yun South Korea 12 698 1.0× 150 0.6× 156 1.0× 94 0.9× 47 0.6× 30 783
Jongwon Choi South Korea 9 871 1.2× 143 0.6× 223 1.4× 200 1.9× 50 0.6× 38 990
David Gerónimo Spain 10 869 1.2× 185 0.8× 142 0.9× 92 0.9× 266 3.5× 11 1.1k

Countries citing papers authored by Volker Eiselein

Since Specialization
Citations

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

Fields of papers citing papers by Volker Eiselein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Volker Eiselein

This figure shows the co-authorship network connecting the top 25 collaborators of Volker Eiselein. A scholar is included among the top collaborators of Volker Eiselein 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 Volker Eiselein. Volker Eiselein 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.
Köppel, Martin, et al.. (2023). A Comprehensive Framework for Evaluating Vision-Based on-Board Rail Track Detection. 1–8. 4 indexed citations
2.
Jacobs, Arne, et al.. (2022). Multi-Sensor Data Annotation Using Sequence-based Active Learning. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 258–263. 2 indexed citations
3.
Αξενόπουλος, Απόστολος, et al.. (2019). A Framework for Large-Scale Analysis of Video \"in the Wild\" to Assist Digital Forensic Examination. IEEE Security & Privacy. 17(1). 23–33. 5 indexed citations
4.
Simon, Maik, et al.. (2018). Scale-Adaptive Real-Time Crowd Detection and Counting for Drone Images. 943–947. 16 indexed citations
5.
Bochinski, Erik, Volker Eiselein, & Thomas Sikora. (2017). High-Speed tracking-by-detection without using image information. 1–6. 430 indexed citations breakdown →
6.
Senst, Tobias, Volker Eiselein, Alexander Kühn, & Thomas Sikora. (2017). Crowd Violence Detection Using Global Motion-Compensated Lagrangian Features and Scale-Sensitive Video-Level Representation. IEEE Transactions on Information Forensics and Security. 12(12). 2945–2956. 62 indexed citations
7.
Eiselein, Volker, Erik Bochinski, & Thomas Sikora. (2017). Assessing post-detection filters for a generic pedestrian detector in a tracking-by-detection scheme. 1–6. 3 indexed citations
8.
Bochinski, Erik, et al.. (2016). Training a convolutional neural network for multi-class object detection using solely virtual world data. Zenodo (CERN European Organization for Nuclear Research). 278–285. 26 indexed citations
9.
Badii, Atta, et al.. (2015). Overview of the MediaEval 2015 Drone Protect Task. MediaEval. 2 indexed citations
10.
Senst, Tobias, Volker Eiselein, & T. Sikora. (2015). A Local Feature based on Lagrangian Measures for Violent Video Classification. 6 (6 .)–6 (6 .). 15 indexed citations
11.
Eiselein, Volker, et al.. (2015). Motion modeling for motion vector coding in HEVC. pp. 154–158. 1 indexed citations
12.
Fradi, Hajer, et al.. (2013). Crowd context-dependent privacy protection filters. 1–6. 7 indexed citations
13.
Senst, Tobias, et al.. (2013). A decentralized privacy-sensitive video surveillance framework. 39. 1–6. 4 indexed citations
14.
Eiselein, Volker, et al.. (2013). Enhancing human detection using crowd density measures and an adaptive correction filter. 2. 19–24. 9 indexed citations
15.
Eiselein, Volker, Tobias Senst, Ianus Keller, & T. Sikora. (2013). A motion-enhanced hybrid Probability Hypothesis Density filter for real-time multi-human tracking in video surveillance scenarios. 2. 6–13. 3 indexed citations
16.
17.
Senst, Tobias, et al.. (2011). On building decentralized wide-area surveillance networks based on ONVIF. 152. 420–423. 6 indexed citations
18.
Senst, Tobias, et al.. (2011). Efficient real-time local optical flow estimation by means of integral projections. 2345–2348. 2 indexed citations
19.
Senst, Tobias, et al.. (2011). Robust modified L<sup>2</sup> local optical flow estimation and feature tracking. 685–690. 13 indexed citations
20.
Senst, Tobias, et al.. (2010). TOWARDS DETECTING PEOPLE CARRYING OBJECTS - A Periodicity Dependency Pattern Approach. 524–529. 3 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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