sac.h

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 * $Id: sac.h 4702 2012-02-23 09:39:33Z gedikli $
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#ifndef PCL_SAMPLE_CONSENSUS_H_
#define PCL_SAMPLE_CONSENSUS_H_

#include "pcl/sample_consensus/sac_model.h"
#include <boost/random.hpp>
#include <ctime>
#include <set>

namespace pcl
{
  template <typename T>
  class SampleConsensus
  {
    typedef typename SampleConsensusModel<T>::Ptr SampleConsensusModelPtr;

    private:
      SampleConsensus () {};

    public:
      typedef boost::shared_ptr<SampleConsensus> Ptr;
      typedef boost::shared_ptr<const SampleConsensus> ConstPtr;

      SampleConsensus (const SampleConsensusModelPtr &model, bool random = false) : sac_model_(model), probability_ (0.99),
                                                               iterations_ (0), threshold_ (DBL_MAX), max_iterations_ (1000)
      {
         // Create a random number generator object
         rng_.reset (new boost::uniform_01<boost::mt19937> (rng_alg_));
         if (random)
           rng_->base ().seed (static_cast<unsigned> (std::time(0)));
         else
           rng_->base ().seed (12345u);
      };

      SampleConsensus (const SampleConsensusModelPtr &model, double threshold, bool random = false) : 
        sac_model_(model), probability_ (0.99), iterations_ (0), threshold_ (threshold), max_iterations_ (1000)
      {
         // Create a random number generator object
         rng_.reset (new boost::uniform_01<boost::mt19937> (rng_alg_));
         if (random)
           rng_->base ().seed (static_cast<unsigned> (std::time(0)));
         else
           rng_->base ().seed (12345u);
       };

      virtual ~SampleConsensus () {};

      inline void 
      setDistanceThreshold (double threshold)  { threshold_ = threshold; }

      inline double 
      getDistanceThreshold () { return (threshold_); }

      inline void 
      setMaxIterations (int max_iterations) { max_iterations_ = max_iterations; }

      inline int 
      getMaxIterations () { return (max_iterations_); }

      inline void 
      setProbability (double probability) { probability_ = probability; }

      inline double 
      getProbability () { return (probability_); }

      virtual bool 
      computeModel (int debug_verbosity_level = 0) = 0;

      inline void
      getRandomSamples (const boost::shared_ptr <std::vector<int> > &indices, 
                        size_t nr_samples, 
                        std::set<int> &indices_subset)
      {
        indices_subset.clear ();
        while (indices_subset.size () < nr_samples)
          //indices_subset.insert ((*indices)[(int) (indices->size () * (rand () / (RAND_MAX + 1.0)))]);
          indices_subset.insert ((*indices)[(int) (indices->size () * rnd ())]);
      }

      inline void 
      getModel (std::vector<int> &model) { model = model_; }

      inline void 
      getInliers (std::vector<int> &inliers) { inliers = inliers_; }

      inline void 
      getModelCoefficients (Eigen::VectorXf &model_coefficients) { model_coefficients = model_coefficients_; }

    protected:
      SampleConsensusModelPtr sac_model_;

      std::vector<int> model_;

      std::vector<int> inliers_;

      Eigen::VectorXf model_coefficients_;

      double probability_;

      int iterations_;
      
      double threshold_;
      
      int max_iterations_;

      boost::mt19937 rng_alg_;

      boost::shared_ptr<boost::uniform_01<boost::mt19937> > rng_;

      inline double
      rnd ()
      {
        return ((*rng_) ());
      }
   };
}

#endif  //#ifndef PCL_SAMPLE_CONSENSUS_H_