Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 199

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

A Bimodal Face and Body Gesture Database for Automatic Analysis of Human Nonverbal Affective Behavior

Open access
Gunes, H., Piccardi, M.·2006·18th International Conference on Pattern Recognition (ICPR'06)

Abstract

To be able to develop and test robust affective multimodal systems, researchers need access to novel databases containing representative samples of human multi-modal expressive behavior. The creation of such databases requires a major effort in the definition of representative behaviors, the choice of expressive modalities, and the collection and labeling of large amount of data. At present, public databases only exist for single expressive modalities such as facial expression analysis. There also exist a number of gesture databases of static and dynamic hand postures and dynamic hand gestures. However, there is not a readily available database combining affective face and body information in a genuine bimodal manner. Accordingly, in this paper, we present a bimodal database recorded by two high-resolution cameras simultaneously for use in automatic analysis of human nonverbal affective behavior

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/icpr.2006.39

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Research works printed but not linked: 17

  1. 0, FGNet Benchmark data
  2. 0, Japanese Female Facial Expression (JAFFE) Database
  3. 0, MMI Face Database
  4. plutchik, 1980, Emotion A Psychoevolutionary Synthesis
  5. 10.1016/j.imavis.2005.09.011 · DOI · Paper page
  6. 10.1109/AFGR.2000.840611 · DOI · Paper page
  7. 10.1145/1101149.1101300 · DOI · Paper page
  8. 0, Massey Hand Gesture Database
  9. balomenos, 2004, Emotion Analysis in Man-Machine Interaction Systems, LNCS, 3361, 318
  10. 10.1007/11573548_114 · DOI
  11. 10.1037/0033-2909.111.2.256 · DOI · Paper page
  12. 10.1016/S1071-5819(03)00047-8 · DOI · Paper page
  13. ekman, 1975, Unmasking the Face A Guide to Recognizing Emotions From Facial Clues
  14. 10.1023/B:JONB.0000023655.25550.be · DOI · Paper page
  15. burgoon, 2005, Augmenting Human Identification of Emotional States in Video, The proceedings of the 4th International Conference on Intelligent Data Analysis
  16. brave, 2002, Emotion in HCI, The HCI Handbook
  17. gunes, 2005, Fusing Face and Body Display for Bi-Modal Emotion Recognition: Single Frame Analysis and Multi-Frame Post Integration, Proc ACII, 102

Cited by

See all 199

Metadata

Authors
Gunes, H., & Piccardi, M.
Venue
18th International Conference on Pattern Recognition (ICPR'06)
Publisher
IEEE
Published
2006
Pages
1148-1153
ISSN
1041-3278 (ISSN-L)
OpenAlex
W1978262206
Cited by
199
References
3
FWCI
16.19
Type
conference paper
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A Bimodal Face and Body Gesture Database for Automatic Analysis of Human Nonverbal Affective Behavior. https://app.cochat.ai/papers/10.1109/icpr.2006.39
The paper
Gunes, H., & Piccardi, M. (2006). A Bimodal Face and Body Gesture Database for Automatic Analysis of Human Nonverbal Affective Behavior. 18th International Conference on Pattern Recognition (ICPR'06). https://doi.org/10.1109/icpr.2006.39

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.