The Dissimilarity-Consensus Tool &
Children Whole-Body Gestures Dataset

This tool implements the dissimilarity-consensus (τ-C) method described in Vatavu (2019), an approach to computing objective measures of consensus (or agreement) between users' gesture preferences to support data analysis in end-user gesture elicitation studies (Wobbrock et al., 2009). The τ-C method models and quantifies the relationship between users' consensus over gesture articulation and numerical measures of gesture dissimilarity, e.g., Dynamic Time Warping or Hausdorff distances, by employing growth curves and logistic functions. Growth curves, such as those illustrated in the figure below, quantify the numerical relationship between consensus (C) and the tolerance in gesture dissimilarity (τ), below which two gestures are considered similar in terms of their articulations.



Supplementary data consisting of illustrations of growth curves and logistic models for the experimental conditions not presented in the CHI paper regarding various dissimilarity functions and aggregators are available here .
Our gesture dataset composed of 1312 whole-body gestures elicited from 30 children, ages 3 to 6 years, is freely available to download for research purposes: dataset.rar .
Our C# and R code implements the dissimilarity-consensus (τ-C) method described in Vatavu (2019) and represents the companion application to our children gestures dataset. The application reads the dataset, visualizes the gestures, computes growth curves and logistic models, and produces the plot visualizations from the paper by running R code. To read and visualize the dataset, the .NET Framework Runtime needs to be installed. To compute logistic curves, R must be installed as well and the path to Rscript.exe must be added to the system PATH environment variable. The video below demonstrates how to use the application:

Related Tools and Publications

The dissimilarity-consensus tool and method relate to previous projects regarding gesture elicitation. The AGreement Analysis Toolkit (AGATe) is an application and associated reusable library (DLL) that supports the user-defined gesture elicitation methodology (Wobbrock et al., 2009). Relevant publications for AGATe are listed below.


We would like to thank Gabriel Cramariuc from the University Stefan cel Mare of Suceava for help with data acquisition.


For any information or suggestion regarding the τ-C tool and method, please contact Prof. Radu-Daniel Vatavu.