Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 219

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Temporal segmentation and activity classification from first-person sensing

Open access
Spriggs, Ekaterina H., De La Torre, Fernando, Hebert, Martial·2009·2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
DOI 10.1109/cvprw.2009.5204354
Open this paper in CoChat — free account

Abstract

Temporal segmentation of human motion into actions is central to the understanding and building of computational models of human motion and activity recognition. Several issues contribute to the challenge of temporal segmentation and classification of human motion. These include the large variability in the temporal scale and periodicity of human actions, the complexity of representing articulated motion, and the exponential nature of all possible movement combinations. We provide initial results from investigating two distinct problems -classification of the overall task being performed, and the more difficult problem of classifying individual frames over time into specific actions. We explore first-person sensing through a wearable camera and inertial measurement units (IMUs) for temporally segmenting human motion into actions and performing activity classification in the context of cooking and recipe preparation in a natural environment. We present baseline results for supervised and unsupervised temporal segmentation, and recipe recognition in the CMU-multimodal activity database (CMU-MMAC).

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/cvprw.2009.5204354

Cites

1 of 1 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 1 references

Research works printed but not linked: 28

  1. 10.1109/ISWC.2005.57 · DOI
  2. 10.1109/TPAMI.2004.1262196 · doi:10.1109/tpami.2004.1262196
  3. 10.1109/BSN.2006.24 · DOI
  4. li, 2002, Motion texture: A twolevel statistical model for character motion synthesis, ACM Trans Graph, 21, 465, 10.1145/566654.566604 · DOI · Paper page
  5. liu, 2006, Segment-based human motion compression. in, ACM SIGGRAPH / Eurographics Symposium on Computer Animation, 127
  6. 10.1145/566570.566607 · DOI · Paper page
  7. lester, 2005, A hybrid discriminative/generative approach for modeling human activities, In Proc of the International Joint Conference on Artificial Intelligence IJCAI, 766
  8. 10.1109/IRDS.2002.1041654 · DOI · Paper page
  9. 10.1145/1015330.1015357 · DOI · Paper page
  10. 10.1023/A:1011139631724 · DOI · Paper page
  11. 10.1007/s11263-007-0122-4 · DOI · Paper page
  12. ormoneit, 2000, Learning and tracking cyclic human motion, NIPS, 894
  13. 10.1109/CVPR.2000.855807 · DOI
  14. schiele, 1999, An interactive computer vision system dypers: Dynamic personal enhanced reality system, Computer Vision Systems, 51, 10.1007/3-540-49256-9_4 · DOI
  15. 10.1109/ICPR.2004.1334462 · DOI · Paper page
  16. 10.1109/CVPR.2007.383170 · doi:10.1109/cvpr.2007.383170
  17. vecchio, 2002, Primitives for human motion: A dynamical approach, 15th IFAC World Congress on Automatic Control
  18. 10.1109/ICCV.2007.4408865 · DOI · Paper page
  19. barbie, 2004, Segmenting motion capture data into distinct behaviors, Graphics Interface, 185
  20. bao, 2004, Activity recognition from userannotated acceleration data, Pervasive Computing, 1, 10.1007/978-3-540-24646-6_1 · DOI · Paper page
  21. 10.1109/MC.2007.154 · DOI
  22. abdelkader, 2002, Motion-based recognition of people in eigengait space, FGR, 1, 267
  23. 10.1109/ICCV.2003.1238420 · DOI · Paper page
  24. de la torre, 2008, Guide to the cmu multimodal activity (cmu-mmac) database, Technical Report CMU-RI-TR-08-22 Robotics Institute Carnegie Mellon University
  25. 10.1109/ICCV.2005.28 · DOI · Paper page
  26. beaudoin, 2008, Motion-motif graphs, ACM SIGGRAPH / Eurographics Symposium on Computer Animation
  27. guerra-filho, 2006, Understanding visuomotor primitives for motion synthesis and analysis, Comp Anim Virtual Worlds, 17, 10.1002/cav.124 · DOI
  28. 10.1023/A:1013254724861 · DOI · Paper page

Cited by

See all 219

Metadata

Authors
Spriggs, E. H., De La Torre, F., & Hebert, M.
Venue
2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Publisher
IEEE
Published
2009-06
Pages
17-24
ISSN
2160-7508 (ISSN-L)
DOI
10.1109/cvprw.2009.5204354
OpenAlex
W2162762857
Cited by
219
References
1
FWCI
6.82
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: Temporal segmentation and activity classification from first-person sensing. https://app.cochat.ai/papers/10.1109/cvprw.2009.5204354
The paper
Spriggs, E. H., De La Torre, F., & Hebert, M. (2009). Temporal segmentation and activity classification from first-person sensing. 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. https://doi.org/10.1109/cvprw.2009.5204354

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.