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Metaphor and Semiotics in (Inter)Action. A motion capture study

Version 1.0

Placiński, Marek; Pleyer, Michael, 2024, "Metaphor and Semiotics in (Inter)Action. A motion capture study", https://doi.org/10.18150/NNLXXT, RepOD, V1

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Description

POLSKI

1. Informacje ogólne

Tytuł zbioru danych: Metafora i Semiotyka w (Inter)Akcji. Badanie z wykorzystaniem technologii przechwytywania ruchu.

Kierownik grantu: dr Michael Pleyer

Współwykonawca: dr Marek Placiński

kontakt: Marek Placiński, marpla@umk.pl

Data zbiórki danych: czerwiec/lipiec 2024

Miejsce zbiórki danych: Toruń, Polska

słowa-klucze: motion capture, semiotyka eksperymentalna, językoznawstwo ewolucyjne, teoria metafory konceptualnej

źródło finansowania: Narodowe Centrum Nauki, program Polonez Bis, umowa nr 2021/43/P/HS2/02729.


2. Opis danych

raw_data_files.zip - zawiera zebrane przez nas dane w postaci "surowej" w formacie .bvh.

csv_data.zip - zawiera zebrane przez nas dane skonwertowane do postaci .csv. Każdy plik .csv zawiera informacje o położeniu czujnika w przestrzeni 3D.

distances.zip - zawiera pliki .csv z wartościami dynamic time warping.

Measures.zip - zawiera pliki .csv z wartościami: objętość, prędkość, zakres ruchu.

all_distances.tab - zawiera wszystkie dane z distances.zip zebrane w jednej tabeli .csv.

data.tab - zawiera wszystkie dane z Measures.zip w jednej tabeli.

pliki o rozszerzeniu .py zawierają kod zastosowany do pozyskania opisanych wyżej danych.

plik o rozszerzeniu .R zawiera analizę ilościową danych.

data utworzenia danych: 15.10.2024


3. Licencja: CC0 1.0 Universal

4. Zbiórka danych

Metodologia: Badani wzięli udział w eksperymencie semiotycznym. Podczas badania komunikowali się za pomocą ruchów ciała o skończonej liczbie znaczeń dosłownych i metaforycznych. W trakcie badania ich ruchy były nagrywane za pomocą technologii motion capture (Rokoko SmartSuit Pro II).

Opis przetwarzania danych: zastosowaliśmy algorytmy dynamic time warping, algorytmy wygładzające szum, obliczyliśmy szybkość ruchu, jego zakres i objętość. Dane zostały następnie przeanalizowane poprzez zastosowanie regresji liniowej.

Kalibracja: uczestnicy byli kaliborwani na początku badania oraz gdy zaszła taka potrzeba (dryft).

5. Informacja o danych

nazwy zmiennych:

velocity - szybkość ruchu, mierzona w cm/ms

path - zakres ruchu, mierzony w cm

distance - dynamic time warping, miara podobieństwa ruchu (im ruch bardziej podobny, tym niższa wartość dynamic time warping)

bbmv - objętość ruchu, mierzona w cm^3

round - runda eksperymentu

ENGLISH

1. General information

Title: Metaphor and Semiotics in (Inter)Action. A motion capture study.

PI: Michael Pleyer, PhD

Co-investigator: Marek Placiński, PhD

contact information: Marek Placiński, marpla@umk.pl

Date of data collection: czerwiec/lipiec 2024

Geographic location of data collection: Toruń, Polska

keywords: motion capture, experimental semiotics, evolutionary linguistics, conceptual metaphor theory

source of funding: National Science Centre, Poland, Polonez Bis program, agreement no 2021/43/P/HS2/02729.


2. Data and file overview

raw_data_files.zip - raw motion data in .bvh format.

csv_data.zip - converted raw files into .csv format. Each .csv file contains information about joint location on a 3D plane.

distances.zip - dynamic time warping .csv files.

Measures.zip - .csv files with the following values: volume, velocity, path.

all_distances.tab - contains data from distances.zip in a single .csv file.

data.tab - contains all Measures.zip data in a single .csv file.

.py files contain the code used to obtain values from distances.zip and Measures.zip

.R file contains data analysis.

The files were created on 15.10.2024


3. Licence: CC0 1.0 Universal

4. Methodological information

Methods: the participant were engaged in an experimental semiotic study. They communicated with the use of gesture and pantomime about a closed space of concrete and metaphorical meanings. Their movement was recorded with the use of motion capture (Rokoko SmartSuit Pro II).

Data processing methods: we used dynamic time warping algorithms, smoothing algorithms, we calculated movement velocity, path and volume. The data was analysed by fitting a linear regression model to the predictors.

5. Data-specific information

names of variables:

velocity - movement velocity, measured in cm/ms

path - movement amplitude, measured in cm

distance - dynamic time warping, a measure of movement si (im ruch bardziej podobny, tym niższa wartość dynamic time warping)

bbmv - bounding box of movement volume, measured in cm^3

round - round of the experiment

(2024)
Subject
Arts and Humanities
Keyword

motion capture, semiotyka eksperymentalna, ewolucja języka, pantomima

CC0 Creative Commons Zero 1.0 CC0 Creative Commons Zero 1.0

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csv_data.zip
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distances.zip
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Measures.zip
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all_distances.tab
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6 Variables, 1625 Observations - UNF:6:tEuErDH+7CohsGj7GCFVPg==
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data.tab
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8 Variables, 3322 Observations - UNF:6:UzyYnGtOq+48VU6l+qk45w==
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data_analysis.R
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kinematic_spaces.py
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conc_distance.py
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prepare_data.py
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sum_up.py
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