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Computer Science
Germany
2025

D-Index & Metrics

Computer Science

D-Index
69
Citations
18384
World Ranking
1981
National Ranking
76

Gerhard Rigoll publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Gerhard Rigoll sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 566 publications — 95th percentile

95% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Gerhard Rigoll D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Gerhard Rigoll sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 69 D-Index — 87th percentile

87% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award
  • 2019 - IEEE Fellow For contributions to multimodal human-machine communication

Overview

Gerhard Rigoll is affiliated with the Technical University of Munich in Germany. Their research primarily focuses on computer science and engineering, with significant contributions in the fields of computer vision and pattern recognition, artificial intelligence, signal processing, biomedical engineering, and aerospace engineering.

The scientist's work covers a variety of topics including:

  • Speech Recognition and Synthesis
  • Speech and Audio Processing
  • Music and Audio Processing
  • Advanced Neural Network Applications
  • Human Pose and Action Recognition
  • Face Recognition and Analysis
  • Video Surveillance and Tracking Methods

Gerhard Rigoll has collaborated frequently with several co-authors, notably Fabian Herzog, Ludwig Kürzinger, Tobias Watzel, Torben Teepe, and Lujun Li, each with more than a dozen joint publications.

The scientist has published extensively, including papers such as:

  • Towards a Deeper Understanding of Skeleton-based Gait Recognition (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • Online Dynamic Hand Gesture Recognition Including Efficiency Analysis (2020), published in IEEE Transactions on Biometrics Behavior and Identity Science
  • How to Design a Three-Stage Architecture for Audio-Visual Active Speaker Detection in the Wild (2021), in the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Cross-Quality LFW: A Database for Analyzing Cross-Resolution Image Face Recognition in Unconstrained Environments (2021), featured at the 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)
  • Improved 3D Object Detector Under Snowfall Weather Condition Based on LiDAR Point Cloud (2022), appearing in the IEEE Sensors Journal

In addition to conference and journal papers, Gerhard Rigoll has contributed to book publications with Springer Science+Business Media. These include the titles Interactive Collaborative Robotics published in both 2020 and 2021.

Publication venues where Rigoll's work frequently appears include arXiv (Cornell University), Lecture Notes in Computer Science, the IEEE International Conference on Automatic Face and Gesture Recognition, IEEE Sensors Journal, and Automotive Innovation.

Recognitions awarded to Gerhard Rigoll include the IEEE Fellow distinction in 2019 for contributions to multimodal human-machine communication.

Best Publications

  • Hidden Markov model-based speech emotion recognition

    B. Schuller;G. Rigoll;M. Lang

  • Background segmentation with feedback: The Pixel-Based Adaptive Segmenter

    Martin Hofmann;Philipp Tiefenbacher;Gerhard Rigoll

  • SVC2004: First International Signature Verification Competition

    Dit-Yan Yeung;Hong Chang;Yimin Xiong;Susan E. George

  • Speech emotion recognition combining acoustic features and linguistic information in a hybrid support vector machine-belief network architecture

    B. Schuller;G. Rigoll;M. Lang

  • Cross-Corpus Acoustic Emotion Recognition: Variances and Strategies

    B Schuller;B Vlasenko;F Eyben;Martin Wöllmer

  • A deep convolutional neural network for video sequence background subtraction

    Mohammadreza Babaee;Duc Tung Dinh;Gerhard Rigoll

  • Acoustic emotion recognition: A benchmark comparison of performances

    Bjorn Schuller;Bogdan Vlasenko;Florian Eyben;Gerhard Rigoll

  • LSTM-Modeling of continuous emotions in an audiovisual affect recognition framework

    Martin WöLlmer;Moritz Kaiser;Florian Eyben;BjöRn Schuller

  • Real-time Hand Gesture Detection and Classification Using Convolutional Neural Networks

    Okan Kopuklu;Ahmet Gunduz;Neslihan Kose;Gerhard Rigoll

  • The TUM Gait from Audio, Image and Depth (GAID) database

    Martin Hofmann;Jürgen Geiger;Sebastian Bachmann;Björn Schuller

  • Multi-view gait recognition using 3D convolutional neural networks

    Thomas Wolf;Mohammadreza Babaee;Gerhard Rigoll

  • High performance real-time gesture recognition using Hidden Markov Models

    G. Rigoll;A. Kosmala;S. Eickeler

  • Speaker adaptation for large vocabulary speech recognition systems using speaker Markov models

    G. Rigoll

  • Resource Efficient 3D Convolutional Neural Networks

    Okan Kopuklu;Neslihan Kose;Ahmet Gunduz;Gerhard Rigoll

  • Recognition of JPEG compressed face images based on statistical methods

    Stefan Eickeler;Stefan Müller;Gerhard Rigoll

  • Being bored? Recognising natural interest by extensive audiovisual integration for real-life application

    Björn Schuller;Ronald Müller;Florian Eyben;Jürgen Gast

  • Gaitgraph: Graph Convolutional Network for Skeleton-Based Gait Recognition

    Torben Teepe;Ali Khan;Johannes Gilg;Fabian Herzog

  • Speaker Independent Emotion Recognition by Early Fusion of Acoustic and Linguistic Features within Ensembles

    Björn W. Schuller;Ronald Müller;Manfred K. Lang;Gerhard Rigoll

  • Combining Long Short-Term Memory and Dynamic Bayesian Networks for Incremental Emotion-Sensitive Artificial Listening

    Martin Wöllmer;Björn Schuller;Florian Eyben;Gerhard Rigoll

  • Speaker Independent Speech Emotion Recognition by Ensemble Classification

    B. Schuller;S. Reiter;R. Muller;M. Al-Hames

  • Hidden Markov model based continuous online gesture recognition

    S. Eickeler;A. Kosmala;G. Rigoll

  • Hidden Markov model-based speech emotion recognition

    Unknown

Frequent Co-Authors

Björn Schuller
Björn Schuller Imperial College London
Martin Wöllmer
Martin Wöllmer Technical University of Munich
Florian Eyben
Florian Eyben Technical University of Munich
Felix Weninger
Felix Weninger Nuance Communications (United States)
Mihai Datcu
Mihai Datcu German Aerospace Center
Shamik Sural
Shamik Sural Indian Institute of Technology Kharagpur
Alex Graves
Alex Graves Google (United States)
Steve Renals
Steve Renals University of Edinburgh
A. N. Rajagopalan
A. N. Rajagopalan Indian Institute of Technology Madras

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