Libras Movement
Donated on 8/16/2009
The data set contains 15 classes of 24 instances each. Each class references to a hand movement type in LIBRAS (Portuguese name 'LÍngua BRAsileira de Sinais', oficial brazilian signal language).
Dataset Characteristics
Multivariate, Sequential
Subject Area
Other
Associated Tasks
Classification, Clustering
Feature Type
Real
# Instances
360
# Features
-
Dataset Information
Additional Information
The dataset (movement_libras) contains 15 classes of 24 instances each, where each class references to a hand movement type in LIBRAS. In the video pre-processing, a time normalization is carried out selecting 45 frames from each video, in according to an uniform distribution. In each frame, the centroid pixels of the segmented objects (the hand) are found, which compose the discrete version of the curve F with 45 points. All curves are normalized in the unitary space. In order to prepare these movements to be analysed by algorithms, we have carried out a mapping operation, that is, each curve F is mapped in a representation with 90 features, with representing the coordinates of movement. Some sub-datasets are offered in order to support comparisons of results.
Has Missing Values?
No
Variables Table
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Additional Variable Information
90 numeric (double) and 1 for the class (integer)
Dataset Files
File | Size |
---|---|
movement_libras.data | 250.6 KB |
movement_libras_10.data | 188 KB |
movement_libras_8.data | 93.9 KB |
movement_libras_5.data | 62.6 KB |
movement_libras_9.data | 31.3 KB |
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset libras_movement = fetch_ucirepo(id=181) # data (as pandas dataframes) X = libras_movement.data.features y = libras_movement.data.targets # metadata print(libras_movement.metadata) # variable information print(libras_movement.variables)
Dias, D., Peres, S., & Bscaro, H. (2009). Libras Movement [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5GC82.
Creators
Daniel Dias
Sarajane Peres
Helton Bscaro
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.