I implemented a bootstrap Particle filter on C++ by reading few Papers and I first implemented a 1D mouse tracker which performed really well. I used normal Gaussian for weighting in this exam.

I extended the algorithm to track face using 2 features of Local motion and HSV 32 bin Histogram. In this example my weighing function becomes the probability of Motion x probability of Histogram. (Is this correct).

Incase if that is correct than I am confused on the resampling function. At the moment my resampling function is as follows:

For each Particle N = 50;

  1. Compute CDF
  2. Generate a random number (via Gaussian) X
  3. Update the particle at index X
  4. Repeat for all N particles.

This is my re-sampling function at the moment. Note: the second step I am using a Random Number via Gaussian distribution for get the index while my weighting function is Probability of Motion and Histogram.

My question is: Should I generate random number using the probability of Motion and Histogram or just the random number via Gaussian is ok.

  • $\begingroup$ You may ask this question on the other places like stackoverflow. because it seems to be a programming issue not a robotic problem. $\endgroup$ – NKN Apr 25 '14 at 15:06

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