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Gesture Phase Segmentation Data Set
Download: Data Folder, Data Set Description
Abstract: The dataset is composed by features extracted from 7 videos with people gesticulating, aiming at studying Gesture Phase Segmentation. It contains 50 attributes divided into two files for each video.
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Data Set Characteristics: |
Multivariate, Sequential, Time-Series |
Number of Instances: |
9900 |
Area: |
N/A |
Attribute Characteristics: |
Real |
Number of Attributes: |
50 |
Date Donated |
2014-06-18 |
Associated Tasks: |
Classification, Clustering |
Missing Values? |
N/A |
Number of Web Hits: |
68139 |
Source:
Creators:
Renata Cristina Barros Madeo (Madeo, R. C. B.)
Priscilla Koch Wagner (Wagner, P. K.)
Sarajane Marques Peres (Peres, S. M.)
{renata.si, priscilla.wagner, sarajane} at usp.br
http://each.uspnet.usp.br/sarajane/
Donor:
University of Sao Paulo - Brazil
Data Set Information:
The dataset is composed by features extracted from 7 videos with people gesticulating, aiming at studying Gesture Phase Segmentation.
Each video is represented by two files: a raw file, which contains the position of hands, wrists, head and spine of the user in each frame; and a processed file, which contains velocity and acceleration of hands and wrists. See the data set description for more information on the dataset.
Attribute Information:
Raw files: 18 numeric attributes (double), a timestamp and a class attribute (nominal).
Processed files: 32 numeric attributes (double) and a class attribute (nominal).
A feature vector with up to 50 numeric attributes can be generated with the two files mentioned above.
Relevant Papers:
1. Madeo, R. C. B. ; Lima, C. A. M. ; PERES, S. M. . Gesture Unit Segmentation using Support Vector Machines: Segmenting
Gestures from Rest Positions. In: Symposium on Applied Computing (SAC), 2013, Coimbra. Proceedings of the 28th Annual
ACM Symposium on Applied Computing (SAC), 2013. p. 46-52.
* In this paper, the videos A1 and A2 were studied.
2. Wagner, P. K. ; PERES, S. M. ; Madeo, R. C. B. ; Lima, C. A. M. ; Freitas, F. A. . Gesture Unit Segmentation Using
Spatial-Temporal Information and Machine Learning. In: 27th Florida Artificial Intelligence Research Society Conference
(FLAIRS), 2014, Pensacola Beach. Proceedings of the 27th Florida Artificial Intelligence Research Society Conference
(FLAIRS). Palo Alto : The AAAI Press, 2014. p. 101-106.
* In this paper, the videos A1, A2, A3, B1, B3, C1 and C3 were studied.
3. Madeo, R. C. B.. Support Vector Machines and Gesture Analysis: incorporating temporal aspects (in Portuguese). Master
Thesis - Universidade de Sao Paulo, Sao Paulo Researcher Foundation. 2013.
* In this document, the videos named B1 and B3 in the document correspond to videos C1 and C3 in this dataset. Only
five videos were explored in this document: A1, A2, A3, C1 and C3.
4. Wagner, P. K. ; Madeo, R. C. B. ; PERES, S. M. ; Lima, C. A. M. . Segmentaçao de Unidades Gestuais com Multilayer
Perceptrons (in Portuguese). In: Encontro Nacional de Inteligencia Artificial e Computacional (ENIAC), 2013, Fortaleza.
Anais do X Encontro Nacional de Inteligencia Artificial e Computacional (ENIAC), 2013.
* In this paper, the videos A1, A2 and A3 were studied.
Citation Request:
Please refer to the Machine Learning Repository's citation policy.
Additionally, the authors require a citation to one or more publications from those cited as relevant papers.
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