public string recognizeGesture(string gestureName, BaseTrajectory trace, out TrajectoryModel.ReasonForFail failReason)
{
//GestureRepresentation.ReasonForFail failReason;
//var calculations = knownGestures.Select((gest,i) => new { GestureName = gest.Key, Similarity = gest.Value.validateGestureTrace(trace, out failReasons[i]) });
double best = 0;
string winner = "";
TrajectoryModel.ReasonForFail tmp;
failReason = TrajectoryModel.ReasonForFail.UNDEFINED;
foreach (var gest in knownGestures)
{
var sim = gest.Value.validateGestureTrace(trace, out tmp);
if (gest.Key == gestureName)
{
failReason = tmp;
}
if (sim > best)
{
best = sim;
winner = gest.Key;
}
}
if (best == 0)
{
return(null);
}
else
{
return(winner);
}
}
public bool authenticateUser(string userName, GestureTrace trace, out TrajectoryModel.ReasonForFail failReason)
{
var targetGesture = knownGestures[userName];
var similarity = targetGesture.validateGestureTrace(trace.LongestStroke, out failReason);
//ToDo: evtl. Schwellwerte hier prüfen?
return(similarity > 0);
}
public static LinkedList <AuthenticationResultRow> validateAuthentication(CHnMMRecognitionSystem system, Dictionary <string, GestureTrace[]> dataSets, int nSubsets)
{
//if(nTrainSets + nTestSets != nSubsets) throw new ArgumentException("Anzahl der Train- und Testsets passt nicht zur angegebenen Anzahl an Subsets");
var results = new LinkedList <AuthenticationResultRow>();
foreach (var entry in dataSets)
{
var trueUser = entry.Key;
var trueUserData = entry.Value;
var subsets = createSubsets(trueUserData, nSubsets);
//Leave one out cross validation: http://en.wikipedia.org/wiki/Cross-validation_%28statistics%29#Leave-one-out_cross-validation
for (int curTestSetIndex = 0; curTestSetIndex < nSubsets; curTestSetIndex++)
{
var trainSet = subsets.Where((ss, i) => i != curTestSetIndex).SelectMany(ss => ss).ToArray();
var testSet = subsets[curTestSetIndex];
//use trainSet to train the model
system.trainGesture(trueUser, trainSet.Select(gt => gt.LongestStroke).ToArray());
//true positives, false negatives, false positives and true negatives
int TP = 0;
int FN = 0;
int FP = 0;
int TN = 0;
int wbfTU = 0;
int wbtTU = 0;
int wbfFU = 0;
int wbtFU = 0;
//calc estimated FRR
foreach (var testTrace in testSet)
{
TrajectoryModel.ReasonForFail reason;
if (!system.authenticateUser(trueUser, testTrace, out reason))
{
FN++;
}
else
{
TP++;
}
if (reason == TrajectoryModel.ReasonForFail.MissedArea)
{
wbfTU++;
}
if (reason == TrajectoryModel.ReasonForFail.MissedTransition)
{
wbtTU++;
}
}
//calc estimated FAR
foreach (var falseData in dataSets)
{
var falseUser = falseData.Key;
var falseUserData = falseData.Value;
if (trueUser == falseUser)
{
continue;
}
TrajectoryModel.ReasonForFail reason = TrajectoryModel.ReasonForFail.UNDEFINED;
foreach (var falseUserTrace in falseUserData)
{
if (!system.authenticateUser(trueUser, falseUserTrace, out reason))
{
TN++;
}
else
{
FP++;
}
}
if (reason == TrajectoryModel.ReasonForFail.MissedArea)
{
wbfFU++;
}
if (reason == TrajectoryModel.ReasonForFail.MissedTransition)
{
wbtFU++;
}
}
//save result
var result = new AuthenticationResultRow();
result.user = trueUser;
result.run = curTestSetIndex;
result.FN = FN;
result.FP = FP;
result.TP = TP;
result.TN = TN;
result.wrongByFormFalseUser = wbfFU;
result.wrongByFormTrueUser = wbfTU;
result.wrongByTimeFalseUser = wbtFU;
result.wrongByTimeTrueUser = wbtTU;
results.AddLast(result);
}
}
return(results);
}
