Spatiotemporal similarity search in 3D motion capture gesture streams

C. Beecks; M. Hassani; J. Hinnell; Daniel Schüller; B. Brenger; I. Mittelberg; T. Seidl

doi:10.1007/978-3-319-22363-6_19

Spatiotemporal similarity search in 3D motion capture gesture streams

C. Beecks, M. Hassani, J. Hinnell, Daniel Schüller, B. Brenger, I. Mittelberg, T. Seidl

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

16 Citations (Scopus)

Abstract

The question of how to model spatiotemporal similarity between gestures arising in 3D motion capture data streams is of major significance in currently ongoing research in the domain of human communication. While qualitative perceptual analyses of co-speech gestures, which are manual gestures emerging spontaneously and unconsciously during face-to-face conversation, are feasible in a small-to-moderate scale, these analyses are inapplicable to larger scenarios due to the lack of efficient query processing techniques for spatiotemporal similarity search. In order to support qualitative analyses of co-speech gestures, we propose and investigate a simple yet effective distance-based similarity model that leverages the spatial and temporal characteristics of co-speech gestures and enables similarity search in 3D motion capture data streams in a query-by-example manner. Experiments on real conversational 3D motion capture data evidence the appropriateness of the proposal in terms of accuracy and efficiency. © Springer International Publishing Switzerland 2015.

Original language	English
Title of host publication	Advances in Spatial and Temporal Databases
Subtitle of host publication	14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings
Editors	C. Claramunt, M. Schneider, R. Chi-Wing Wong, L. Xiong, W.-K. Loh, C. Shahabi, K.-J. Li
Publisher	Springer
Pages	355-372
Number of pages	18
ISBN (Electronic)	978-3-319-22363-6
ISBN (Print)	978-3-319-22362-9
DOIs	https://doi.org/10.1007/978-3-319-22363-6_19
Publication status	Published - 2015
Externally published	Yes
Event	14th International Symposium on Spatial and Temporal Databases (SSTD) - Hong Kong University of Science, Hong Kong, China Duration: 26 Aug 2015 → 28 Aug 2015 Conference number: 14 http://sstd2015.org/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9239

Conference

Conference	14th International Symposium on Spatial and Temporal Databases (SSTD)
Abbreviated title	SSTD 2015
Country/Territory	China
City	Hong Kong
Period	26/08/15 → 28/08/15
Internet address	http://sstd2015.org/

Keywords

3D motion capture data
Co-speech gestures
Dynamic time warping
Gesture matching distance
Gesture signature
Similarity search
Spatiotemporal data
Streams

Access to Document

10.1007/978-3-319-22363-6_19

http://www.mendeley.com/research/spatiotemporal-similarity-search-3d-motion-capture-gesture-streams

Cite this

Beecks, C., Hassani, M., Hinnell, J., Schüller, D., Brenger, B., Mittelberg, I., & Seidl, T. (2015). Spatiotemporal similarity search in 3D motion capture gesture streams. In C. Claramunt, M. Schneider, R. Chi-Wing Wong, L. Xiong, W-K. Loh, C. Shahabi, & K-J. Li (Eds.), Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings (pp. 355-372). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9239). Springer. https://doi.org/10.1007/978-3-319-22363-6_19

Beecks, C. ; Hassani, M. ; Hinnell, J. et al. / Spatiotemporal similarity search in 3D motion capture gesture streams. Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings. editor / C. Claramunt ; M. Schneider ; R. Chi-Wing Wong ; L. Xiong ; W.-K. Loh ; C. Shahabi ; K.-J. Li. Springer, 2015. pp. 355-372 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{8cb834acd8d14ffd98b10fe855c28ea1,

title = "Spatiotemporal similarity search in 3D motion capture gesture streams",

abstract = "The question of how to model spatiotemporal similarity between gestures arising in 3D motion capture data streams is of major significance in currently ongoing research in the domain of human communication. While qualitative perceptual analyses of co-speech gestures, which are manual gestures emerging spontaneously and unconsciously during face-to-face conversation, are feasible in a small-to-moderate scale, these analyses are inapplicable to larger scenarios due to the lack of efficient query processing techniques for spatiotemporal similarity search. In order to support qualitative analyses of co-speech gestures, we propose and investigate a simple yet effective distance-based similarity model that leverages the spatial and temporal characteristics of co-speech gestures and enables similarity search in 3D motion capture data streams in a query-by-example manner. Experiments on real conversational 3D motion capture data evidence the appropriateness of the proposal in terms of accuracy and efficiency. {\textcopyright} Springer International Publishing Switzerland 2015.",

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author = "C. Beecks and M. Hassani and J. Hinnell and Daniel Sch{\"u}ller and B. Brenger and I. Mittelberg and T. Seidl",

year = "2015",

doi = "10.1007/978-3-319-22363-6_19",

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editor = "C. Claramunt and M. Schneider and {Chi-Wing Wong}, R. and L. Xiong and W.-K. Loh and C. Shahabi and K.-J. Li",

booktitle = "Advances in Spatial and Temporal Databases",

address = "Germany",

note = "14th International Symposium on Spatial and Temporal Databases (SSTD), SSTD 2015 ; Conference date: 26-08-2015 Through 28-08-2015",

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Beecks, C, Hassani, M, Hinnell, J, Schüller, D, Brenger, B, Mittelberg, I & Seidl, T 2015, Spatiotemporal similarity search in 3D motion capture gesture streams. in C Claramunt, M Schneider, R Chi-Wing Wong, L Xiong, W-K Loh, C Shahabi & K-J Li (eds), Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9239, Springer, pp. 355-372, 14th International Symposium on Spatial and Temporal Databases (SSTD), Hong Kong, China, 26/08/15. https://doi.org/10.1007/978-3-319-22363-6_19

Spatiotemporal similarity search in 3D motion capture gesture streams. / Beecks, C.; Hassani, M.; Hinnell, J. et al.
Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings. ed. / C. Claramunt; M. Schneider; R. Chi-Wing Wong; L. Xiong; W.-K. Loh; C. Shahabi; K.-J. Li. Springer, 2015. p. 355-372 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9239).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Spatiotemporal similarity search in 3D motion capture gesture streams

AU - Beecks, C.

AU - Hassani, M.

AU - Hinnell, J.

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AU - Brenger, B.

AU - Mittelberg, I.

AU - Seidl, T.

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N2 - The question of how to model spatiotemporal similarity between gestures arising in 3D motion capture data streams is of major significance in currently ongoing research in the domain of human communication. While qualitative perceptual analyses of co-speech gestures, which are manual gestures emerging spontaneously and unconsciously during face-to-face conversation, are feasible in a small-to-moderate scale, these analyses are inapplicable to larger scenarios due to the lack of efficient query processing techniques for spatiotemporal similarity search. In order to support qualitative analyses of co-speech gestures, we propose and investigate a simple yet effective distance-based similarity model that leverages the spatial and temporal characteristics of co-speech gestures and enables similarity search in 3D motion capture data streams in a query-by-example manner. Experiments on real conversational 3D motion capture data evidence the appropriateness of the proposal in terms of accuracy and efficiency. © Springer International Publishing Switzerland 2015.

AB - The question of how to model spatiotemporal similarity between gestures arising in 3D motion capture data streams is of major significance in currently ongoing research in the domain of human communication. While qualitative perceptual analyses of co-speech gestures, which are manual gestures emerging spontaneously and unconsciously during face-to-face conversation, are feasible in a small-to-moderate scale, these analyses are inapplicable to larger scenarios due to the lack of efficient query processing techniques for spatiotemporal similarity search. In order to support qualitative analyses of co-speech gestures, we propose and investigate a simple yet effective distance-based similarity model that leverages the spatial and temporal characteristics of co-speech gestures and enables similarity search in 3D motion capture data streams in a query-by-example manner. Experiments on real conversational 3D motion capture data evidence the appropriateness of the proposal in terms of accuracy and efficiency. © Springer International Publishing Switzerland 2015.

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KW - Gesture matching distance

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KW - Similarity search

KW - Spatiotemporal data

KW - Streams

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DO - 10.1007/978-3-319-22363-6_19

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SN - 978-3-319-22362-9

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Advances in Spatial and Temporal Databases

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A2 - Schneider, M.

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A2 - Xiong, L.

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A2 - Shahabi, C.

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Beecks C, Hassani M, Hinnell J, Schüller D, Brenger B, Mittelberg I et al. Spatiotemporal similarity search in 3D motion capture gesture streams. In Claramunt C, Schneider M, Chi-Wing Wong R, Xiong L, Loh W-K, Shahabi C, Li K-J, editors, Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings. Springer. 2015. p. 355-372. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-22363-6_19

Spatiotemporal similarity search in 3D motion capture gesture streams

Abstract

Publication series

Conference

Keywords

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