A toolbox for QTC computations
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.gitignore
EditDist.m
LICENSE
README.md
crossValidation.m
graph_to_dot.m
orthogonalLine.m
qtc2case.m
qtc2hmm.m
qtcCND.m
qtcCase2Label.m
qtcDist.m
qtcMarkovDot.m
qtcMostProbableTrace.m
qtcNum2Str.m
qtcPlotPoses.m
qtcSeq.m
qtcSeqDecode.m
qtcSmoothing.m
qtcTrainHmm.m
qtcTransProb.m
qtcTranslate.m
qtcc.m

README.md

qtc-toolbox

A toolbox for QTC_c computations

QTC representation

  • A QTC_c sequence is represented as a matrix
    • with 4 columns indicating QTC elements (human-dist, robot-dist, human-side, robot-side)
    • with as many rows as the sequence has states
    • two successively occurring same states should be collapsed into one
  • a set of QTC_c sequences is represented as a one-dimensional cell array of QTC sequences

Existing functions

  • qtc2case converts a given QTC sequence matrix into a one-dimensional stream of case identifiers (numbered 1-49)
  • qtc2hmm computes the transition probabilities of a set of QTC sequences to form a Markov model with added start and end states. Uses the standard Matlab HMM functions.
  • qtcDist computes the QTC edit distance between either all pairs in a set (when invoked with one arg) or two explicitly given sequences
  • qtcMarkovDot create a visualisation in GraphViz of the transition probablilities
  • qtcSeqDecode can compute the likelihood of a given sequence allowing for automatic classification

Some useful case:

plot

% create without pseudo state transitions (useful for plotting)
hmm=qtc2hmm(overtake_ns,0.0)
qtcMarkovDot(hmm)
! dot -Tps tmp.dot > out.ps

classifiy

% create with pseudo transitions
hmm=qtc2hmm(overtake_ns)
% compute the likelihood for a given sequnce:
qtcSeqDecode(hmm,overtake_s{4})