Description Usage Format Source
The dataset is composed of features extracted from 7 videos with people gesticulating, aiming at studying gesture phase segmentation. It contains velocity and acceleration recording of the experimental subjects' hands and wrists.
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A data frame with 1743 observations on the following 33 variables.
Vectorial velocity of left hand (x coordinate)
Vectorial velocity of left hand (y coordinate)
Vectorial velocity of left hand (z coordinate)
Vectorial velocity of right hand (x coordinate)
Vectorial velocity of right hand (y coordinate)
Vectorial velocity of right hand (z coordinate)
Vectorial velocity of left wrist (x coordinate)
Vectorial velocity of left wrist (y coordinate)
Vectorial velocity of left wrist (z coordinate)
Vectorial velocity of right wrist (x coordinate)
Vectorial velocity of right wrist (y coordinate)
Vectorial velocity of right wrist (z coordinate)
Vectorial acceleration of left hand (x coordinate)
Vectorial acceleration of left hand (y coordinate)
Vectorial acceleration of left hand (z coordinate)
Vectorial acceleration of right hand (x coordinate)
Vectorial acceleration of right hand (y coordinate)
Vectorial acceleration of right hand (z coordinate)
Vectorial acceleration of left wrist (x coordinate)
Vectorial acceleration of left wrist (y coordinate)
Vectorial acceleration of left wrist (z coordinate)
Vectorial acceleration of right wrist (x coordinate)
Vectorial acceleration of right wrist (y coordinate)
Vectorial acceleration of z coordinate (z coordinate)
Scalar velocity of left hand
Scalar velocity of right hand
Scalar velocity of left hand
Scalar velocity of right wrist
Scalar velocity of left hand
Scalar velocity of right hand
Scalar velocity of left wrist
Scalar velocity of right wrist
Phase
Phase of gesture: D(rest position),P(preparation),S(stroke),H(hold),R(retraction)
https://archive.ics.uci.edu/ml/datasets/gesture+phase+segmentation#
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.
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.
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