Method update

tracking/src/track_object.cpp:146–246

}

void
TrackObject::update(
    double x,
    double y,
    double z,
    double height,
    double distance,
    std::string object_name,
    double data_assocation_score,
    double confidence,
    double min_confidence,
    double min_confidence_detections,
    open_ptrack::detection::DetectionSource* detection_source,
    bool first_update)
{
  //Update Kalman filter
  int difference;
  double vx, vy;
  if (velocity_in_motion_term_)
  {
    ros::Duration d(1.0);
    ros::Duration d2(2.0);

    double t = std::max(first_time_detected_.toSec(), (detection_source->getTime() - d).toSec());
    t = std::min(t, last_time_detected_.toSec());
    t = std::max(t, (detection_source->getTime() - d2).toSec());
    double dt = t - last_time_predicted_.toSec();

    difference = int(round(dt / period_));
    int vIndex = (MAX_SIZE + last_time_predicted_index_ + difference) % MAX_SIZE;

    if(difference != 0)
    {
      vx = - (x - mahalanobis_map4d_[vIndex].x) / dt;
      vy = - (y - mahalanobis_map4d_[vIndex].y) / dt;
    }
    else
    {
      vx = mahalanobis_map4d_[vIndex].x;
      vy = mahalanobis_map4d_[vIndex].x;
    }
  }

  // Update Kalman filter from the last time the track was visible:
  int framesLost = int(round((detection_source->getTime() - last_time_detected_).toSec() / period_)) - 1;

  for(int i = 0; i < framesLost; i++)
  {
    filter_->predict();
    filter_->update();
  }

  filter_->predict();
  if (velocity_in_motion_term_)
  {
    filter_->update(x, y, vx, vy, distance);
  }
  else