Understanding the Gap between 2D and 3D Skeleton-Based Action Recognition

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00107709" target="_blank" >RIV/00216224:14330/19:00107709 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ISM46123.2019.00041" target="_blank" >http://dx.doi.org/10.1109/ISM46123.2019.00041</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ISM46123.2019.00041" target="_blank" >10.1109/ISM46123.2019.00041</a>

Result language
angličtina
Original language name
Understanding the Gap between 2D and 3D Skeleton-Based Action Recognition
Original language description
Large volumes of RGB video data are recorded and processed every day. One of the embedded data modality within these videos is the information about human motions. Up to now, this information has been almost unfeasible to extract, and thus human-motion understanding research has been mainly limited to 3D skeleton data captured by dedicated hardware only. However, with recent advances in computer vision, it is possible to estimate 2D skeleton sequences from ordinary videos quite accurately. Such 2D skeleton data possess an excellent potential for future motion understanding applications. In this paper, we adopt a state-of-the-art bidirectional LSTM network to analyze the accuracy gap in the expressive power of 2D and 3D skeleton data recorded simultaneously on a high number of 20k human actions. We further examine how the missing depth information and fluctuations in 2D skeleton sizes influence the recognition rate. We also demonstrate the suitability of 2D skeleton data for general daily activity recognition by reporting baselines on the PKU-MMD dataset.
Czech name
—
Czech description
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Project
<a href="/en/project/GA19-02033S" target="_blank" >GA19-02033S: Searching, Mining, and Annotating Human Motion Streams</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
21st IEEE International Symposium on Multimedia (ISM)
ISBN
9781728156064
ISSN
—
e-ISSN
—
Number of pages
4
Pages from-to
192-195
Publisher name
IEEE Computer Society
Place of publication
Neuveden
Event location
San Diego, California, USA
Event date
Jan 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000528909200030

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