/**
* After the command is complete, update the matrices
* with detected gestures.
*/
public void update_confusion_matrices(ConfusionMatrices cm)
{
bool found = false;
for (int ii = 0;
ii < detected_ids.Count;
ii++)
{
int detected_id = detected_ids[ii];
if (found && expected_id == detected_id)
{
// treat as false positive
// because we've already detected
// the gesture once
cm.AddResult(
expected_id,
-2);
continue;
}
cm.AddResult(
expected_id,
detected_id);
// mark that we've found this gesture
found = found || (detected_id == expected_id);
}
// false negative
if (!found)
{
cm.AddResult(
expected_id,
-1);
}
}
/**
* A simple user independent test.
*/
public static void user_indepedent_test(DeviceType device)
{
// First, load all training data for one device type.
string path = "";
if (device == DeviceType.KINECT)
{
path = Global.GetRootDirectory() + "datasets/jk2017/kinect/training/";
}
else if (device == DeviceType.LEAP_MOTION)
{
path = Global.GetRootDirectory() + "datasets/jk2017/leap_motion/training/";
}
Dataset ds = Dataset.LoadDataset(path);
int subject_cnt = ds.Subjects.Count;
int sample_cnt = ds.Samples.Count;
ConfusionMatrices cm = new ConfusionMatrices(ds);
// iterate through all subjects
for (int subject_id = 0; subject_id < subject_cnt; subject_id++)
{
ConfusionMatrices cm_individual = new ConfusionMatrices(ds);
Console.WriteLine("Participant: " + subject_id);
// train a recognizer with the selected subject
JackknifeBlades blades = new JackknifeBlades();
blades.SetIPDefaults();
Jackknife jk = new Jackknife(blades);
for (int sample_id = 0; sample_id < sample_cnt; sample_id++)
{
Sample sample = ds.Samples[sample_id];
if (sample.SubjectId != subject_id)
{
continue;
}
jk.AddTemplate(ds.Samples[sample_id]);
}
// only train the recognize if you need
// test the recognizer with all other samples
for (int sample_id = 0; sample_id < sample_cnt; sample_id++)
{
Sample sample = ds.Samples[sample_id];
if (sample.SubjectId == subject_id)
{
continue;
}
int gid = jk.Classify(sample);
cm_individual.AddResult(
sample.GestureId,
gid);
}
cm.AddResult(cm_individual);
ResultT resultss = cm_individual.Results();
resultss.Print();
}
Console.WriteLine("Aggregate Results: ");
ResultT results = cm.Results();
results.Print();
}