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WEBENCH® Tools/TDA3XEVM: TDA3x

Part Number: TDA3XEVM

Tool/software: WEBENCH® Design Tools

Hi,Guys.I am using tda3x to do the Pedestrian Detection in TDA3x.I am trying with the adaboost with ACF.I have already sucessfully used the usecase you provide.And I replace the outcome with my own(produced by the matlab tool box from https://github.com/tidsp/acf-jacinto). My question is:

1

In  acfJacintoTrainTest.m we have two parameters:opts.modelDs and opts.modelDsPad the default values are as follows:

%opts.modelDs=[100 41]; opts.modelDsPad=[128 64];
%opts.modelDs=[56 24]; opts.modelDsPad=[64 32];
opts.modelDs=[56 24]; opts.modelDsPad=[64 64];

If I change the opts.modelDsPad to some other value like [66 34],the dsp can not use the outcome of matlab.Is this common?If I want to change these parameters,how should I do?

2.

According to adaboost,every detected window(Pedestrian) has a score above 0(ignore the window with a score below 0),If I want to set the score above say 4 to be 0.By this means I want to reduce the false positive(I know I will also reduce the recall).I can do it in matlab in the detect process,but how should I do this process in TDA3x?Thank you!  

  • Hi,

    Currently, the model sizes are hard-coded and you will have to change source code to change the model sizes. However, it is possible to change the score thresholds.

    I have forwarded this to an expert who will give you more details.

    Best regards,

  • You can use the flags strongCascadeTh and softCascadeTh to control the false detections.

    strongCasdadeTh is a hard threshold which will not allow any detections which a score less than the set value

    softCascadeTh is mostly for early exit, this will prevent unnecessary tree traversals for candidates whose score cannot improve above this value.

    Both these values can be set in the user config file "object_detection.cfg". Each type of object has separate thresholds (PD, VD, TSR)

    Regards,
    Shyam