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Biomotion Toolbox

Biological motion research is an increasingly active field, with a great potential to contribute to a wide range of applications, such as behavioral monitoring/motion detection in surveillance situations, intention inference in social interactions, and diagnostic tools in autism research. In recent years, a large amount of motion capture data has become freely available online, potentially providing rich stimulus sets for biological motion research. However, there currently does not exist an easy-to-use tool to extract, present and manipulate motion capture data in the MATLAB environment, which many researchers use to program their experiments. We have developed the Biomotion Toolbox, which allows researchers to import motion capture data in a variety of formats, to display actions using Psychtoolbox 3, and to manipulate action displays in specific ways (e.g., invertion, 3D rotation, spatial-scrambling, phase-scrambling, and limited lifetime). The toolbox was designed to allow researchers with a minimal level of MATLAB programming skills to code experiments using biological motion stimuli. Download the Biomotion toolbox here.

 

Human action online database

CMU Graphics Lab Motion Capture Database with six motion categories and >100 motion sequences http://mocap.cs.cmu.edu/

Point-light display movies from Dr. Thomas Shipley's lab. http://astro.temple.edu/~tshipley/mocap/dotMovie.html

 

Causal reasoning

Matlab code for simulating models of human causal induction, used in Lu, H., Yuille, A., Liljeholm, M., Cheng, P. W., Holyoak, K. J. (2008). Bayesian generic priors for causal learning. Psychological Review, 115(4), 955-984. [PDF]

Version 1: [MATLAB CODE 1] required basic MATLAB software for simulation

Version 2: [MATLAB CODE 2] require MATLAB Symbolic Toolbox, but with faster computation ]

 

Analogical inference

Matlab code for Holyoak, K. J., Lee, H. S., & Lu, H. (2010). Analogical and category-based inference: A theoretical integration with Bayesian causal models. Journal of Experimental Psychology: General, 139(4), 702-27. [PDF] Note: require MATLAB Symbolic Toolbox.

 

Relation learning: BART

Matlab code for BART. Lu, H., Chen, D., & Holyoak, H. J. (2012). Bayesian analogy with relational transformations. Psychological Review, 119(3), 617-648. [PDF]

 

Statistical test tools

Test of Mardia’s coefficients of multivariate skewness and kurtosis

J. Arthur Woodward and Hongjing Lu

MATLAB code: [download]

Reference: Bonett, D.G., Woodward, J. A. Woodward, Randall, R. L. Estimating p-values for Mardia’s coefficients of multivariate skewness and kurtosis. Computational Statistics, 17 (1), 117-121. 2002.

 

Modelling Study Group

MATLAB Parallel Computing Toolbox Tutorial, Matthew Weiden, 1/26/2010