Tool/software: TI C/C++ Compiler
Hi,
I am learning people counting's gtrack.I have the following questions:
1.In the prediction step of EKF,
Q is the process noise covariance matrix.And we consider piecewise white noise model for the noise.
We define maxAcceleration 5m/s according to your demo.What is the basis for setting the value?
In gtrackUnitPredict function,obj.P_apriori(1:mSize,1:mSize) = obj.F(1:mSize,1:mSize) * obj.P(1:mSize,1:mSize) * obj.F(1:mSize,1:mSize)' + obj.Q(1:mSize,1:mSize)*obj.processVariance
processVariance = (0.5f*maxAcceleration)*(0.5f*maxAcceleration).Why is maxAcceleration multiplied by 0.5?
2.In gtrackUnitScore function,we compute the Mahalanobis distance between all measurements of cloud point and different tracks.
1)We build a gate using gtrack_gateCreateLim function.
gC_inv (EC) is the inverse of group covariance matrix(gC).Sometimes,the main diagonal of the matrix(gC_inv) is negative (gC's is positive).Is it right?Can the gate be negative?
2)
We use gtrack_computeMahalanobis3 function to compute mahalanobis distance.Still,the main diagonal of the matrix(gC_inv) is sometimes negative.
Can the mahalanobis distance be negative?
Thanks,
Hanna