private bool UpdateGreaterThanThreshold(InternalToken token)
{
if (Math.Abs(token.DeltaPosition.x) > TokenUpdateTranslationThreshold || Math.Abs(token.DeltaPosition.y) > TokenUpdateTranslationThreshold ||
Math.Abs(token.DeltaAngle) > TokenUpdateRotationThreshold)
{
return(true);
}
else
{
return(false);
}
}
internal Token(InternalToken internalToken, bool MeanSquare)
{
this._id = internalToken.Id;
this._class = internalToken.Class;
if (!MeanSquare)
{
this._position = internalToken.Position;
this._angle = internalToken.Angle;
this._deltaAngle = internalToken.DeltaAngle;
this._deltaPosition = internalToken.DeltaPosition;
}
else
{
this._position = internalToken.MeanSquarePosition;
this._angle = internalToken.MeanSquareAngle;
this._deltaAngle = internalToken.MeanSquareDeltaAngle;
this._deltaPosition = internalToken.MeanSquareDeltaPosition;
}
}
private void IdentifyCluster(Cluster cluster)
{
//TODO this function requires updates
Profiler.BeginSample("---TokenEngine : Token Identification");
InternalToken token = TokenIdentification.Instance.IdentifyCluster(cluster);
Profiler.EndSample();
if (token != null)
{
//Statistics
tokenStatistics.TokenIdentification(true);
//Calculate TokenClass
Profiler.BeginSample("---TokenEngine: Class LUT");
token.ComputeTokenClass(ClassComputeRefSystem, ComputeDimension);
Profiler.EndSample();
tokenStatistics.TokenClassRecognition(token.Class);
//Cluster Identification was succesfull
//Set Token ID
token.SetTokenId(GetFirstAvailableTokenId());
tokenIds.Add(token.Id);
//Add Token to internal List
tokens.Add(token.HashId, token);
//Add Token To Global List
InputManager.AddToken(new Token(token, ContinuousMeanSquare));
//Add Token TO local buffer
succesfullyIdentifiedTokens.Add(token);
}
else
{
tokenStatistics.TokenIdentification(false);
//Add token to local buffer
failedIdentifiedCluster.Add(cluster);
}
}
internal Token(InternalToken internalToken, bool MeanSquare)
{
this._id = internalToken.Id;
this._class = internalToken.Class;
if (!MeanSquare)
{
this._position = internalToken.Position;
this._angle = internalToken.Angle;
this._deltaAngle = internalToken.DeltaAngle;
this._deltaPosition = internalToken.DeltaPosition;
}
else
{
this._position = internalToken.MeanSquarePosition;
this._angle = internalToken.MeanSquareAngle;
this._deltaAngle = internalToken.MeanSquareDeltaAngle;
this._deltaPosition = internalToken.MeanSquareDeltaPosition;
}
}
internal static void AddToken(InternalToken token)
{
_tokens[token.Id] = new Token(token,TokenManager.Instance.ContinuousMeanSquare);
}
public InternalToken IdentifyCluster(Cluster cluster)
{
InternalToken token = null;
bool originFound, axisDistinguished;
//Cluster identification Algorithm
Dictionary <int, TouchInput> clusterPoints = cluster.Points;
TokenMarker[] meanSquaredTokenReferenceSystem;
/*Ordered indexes of markers 0 => Origin
* 1 => X axis
* 2 => Y axis
* 3 => Data
*/
int[] orderedIndexes = new int[4];
//Find two furthest apart poits which reppresent the x xis and the y axis markers
Profiler.BeginSample("------Token Identification : Find Two Furthest Point");
int[] furthestPointIndexes = FindTwoFurthestPoints(clusterPoints.Values.ToArray());
Profiler.EndSample();
//Gets indexes of two remaing points which reppresent origin and data marker
int[] originAndDataIndexes = clusterPoints.Where(p => p.Key != furthestPointIndexes[0] && p.Key != furthestPointIndexes[1])
.Select(z => z.Key).ToArray();
Profiler.BeginSample("------Token Identification : Find Origin");
originFound = FindOriginIndex(furthestPointIndexes, originAndDataIndexes, clusterPoints, ref orderedIndexes);
Profiler.EndSample();
if (originFound)
{
//Origin Marker Identified and stored in orderedIndexes[0]
Profiler.BeginSample("------Token Identification : Distinguish Axis");
axisDistinguished = DistinguishAxisVectors(furthestPointIndexes, clusterPoints, ref orderedIndexes);
Profiler.EndSample();
if (axisDistinguished)
{
//Axis markers have been correctly identified
//Remaing point is Data Marker
orderedIndexes[3] = clusterPoints.Where(p => p.Key != orderedIndexes[0] && p.Key != orderedIndexes[1] && p.Key != orderedIndexes[2])
.Select(z => z.Key).Single();
//Compute Mean Square Problem for reference System
Dictionary <int, TokenMarker> markers = TokenUtils.ConvertTouchInputToMarkers(orderedIndexes, clusterPoints);
Profiler.BeginSample("------Token Identification: MeanSquare Calcs");
meanSquaredTokenReferenceSystem = TokenUtils.MeanSquareOrthogonalReferenceSystem(markers[orderedIndexes[0]],
markers[orderedIndexes[1]],
markers[orderedIndexes[2]],
TokenManager.CurrentTokenType.DistanceOriginAxisMarkersPX);
Profiler.EndSample();
Profiler.BeginSample("------Token Identification: MeanSquare Calcs Maxima");
TokenMarker[] meanSquaredTokenReferenceSystemOptimized = TokenUtils.MeanSquareOrthogonalReferenceSystemOptimized(markers[orderedIndexes[0]],
markers[orderedIndexes[1]],
markers[orderedIndexes[2]],
TokenManager.CurrentTokenType.DistanceOriginAxisMarkersPX);
Profiler.EndSample();
//Create Token
token = new InternalToken(cluster.Hash, markers);
token.SetMeanSquareReferenceSystem(meanSquaredTokenReferenceSystem);
}
}
else
{
//No orthogonal vectors found thus no origin, failed identification
//For the moment return null, in case consider doing second iteration on second maximum
return(token);
}
return(token);
}
private bool UpdateGreaterThanThreshold(InternalToken token)
{
if (Math.Abs(token.DeltaPosition.x) > TokenUpdateTranslationThreshold || Math.Abs(token.DeltaPosition.y) > TokenUpdateTranslationThreshold ||
Math.Abs(token.DeltaAngle) > TokenUpdateRotationThreshold)
return true;
else
return false;
}
public InternalToken IdentifyCluster(Cluster cluster)
{
InternalToken token = null;
bool originFound, axisDistinguished;
//Cluster identification Algorithm
Dictionary<int, TouchInput> clusterPoints = cluster.Points;
TokenMarker[] meanSquaredTokenReferenceSystem;
/*Ordered indexes of markers 0 => Origin
* 1 => X axis
* 2 => Y axis
* 3 => Data
*/
int[] orderedIndexes = new int[4];
//Find two furthest apart poits which reppresent the x xis and the y axis markers
Profiler.BeginSample("------Token Identification : Find Two Furthest Point");
int[] furthestPointIndexes = FindTwoFurthestPoints(clusterPoints.Values.ToArray());
Profiler.EndSample();
//Gets indexes of two remaing points which reppresent origin and data marker
int[] originAndDataIndexes = clusterPoints.Where(p => p.Key != furthestPointIndexes[0] && p.Key != furthestPointIndexes[1])
.Select(z => z.Key).ToArray();
Profiler.BeginSample("------Token Identification : Find Origin");
originFound = FindOriginIndex(furthestPointIndexes, originAndDataIndexes, clusterPoints, ref orderedIndexes);
Profiler.EndSample();
if (originFound)
{
//Origin Marker Identified and stored in orderedIndexes[0]
Profiler.BeginSample("------Token Identification : Distinguish Axis");
axisDistinguished = DistinguishAxisVectors(furthestPointIndexes, clusterPoints, ref orderedIndexes);
Profiler.EndSample();
if (axisDistinguished)
{
//Axis markers have been correctly identified
//Remaing point is Data Marker
orderedIndexes[3] = clusterPoints.Where(p => p.Key != orderedIndexes[0] && p.Key != orderedIndexes[1] && p.Key != orderedIndexes[2])
.Select(z => z.Key).Single();
//Compute Mean Square Problem for reference System
Dictionary<int, TokenMarker> markers = TokenUtils.ConvertTouchInputToMarkers(orderedIndexes, clusterPoints);
Profiler.BeginSample("------Token Identification: MeanSquare Calcs");
meanSquaredTokenReferenceSystem = TokenUtils.MeanSquareOrthogonalReferenceSystem(markers[orderedIndexes[0]],
markers[orderedIndexes[1]],
markers[orderedIndexes[2]],
TokenManager.CurrentTokenType.DistanceOriginAxisMarkersPX);
Profiler.EndSample();
Profiler.BeginSample("------Token Identification: MeanSquare Calcs Maxima");
TokenMarker[] meanSquaredTokenReferenceSystemOptimized = TokenUtils.MeanSquareOrthogonalReferenceSystemOptimized(markers[orderedIndexes[0]],
markers[orderedIndexes[1]],
markers[orderedIndexes[2]],
TokenManager.CurrentTokenType.DistanceOriginAxisMarkersPX);
Profiler.EndSample();
//Create Token
token = new InternalToken(cluster.Hash, markers);
token.SetMeanSquareReferenceSystem(meanSquaredTokenReferenceSystem);
}
}
else
{
//No orthogonal vectors found thus no origin, failed identification
//For the moment return null, in case consider doing second iteration on second maximum
return token;
}
return token;
}
