void SiftHough :: vote(SiftPointMatchConstPtr match)
{
std::list<HoughPoint> points;
houghpointsFromMatch(points, match);
QMutexLocker locker(&m_lock);
foreach_const_it(it, points, std::list<HoughPoint>)
m_clusters[*it].push_back(match);
}
double estimate_lognormal(const std::map<double,double>& distrib,
LogNormalDistrib::Params& init)
{
typedef std::map<double,double> distrib_type;
double n = distrib_size(distrib);
double mu = 0.0;
foreach_const_it(it, distrib, distrib_type)
mu += log(it->first)*it->second;
mu /= n;
double dev = 0;
foreach_const_it(it, distrib, distrib_type)
{
double t = log(it->first)-mu;
dev += t*t*it->second;
}
weibull_upper_bounds_function(const distrib_type& distrib,
WeibullEstimates estimates,
double confidence,
double c)
: vnl_cost_function(2), // 2 parameters
distrib(distrib),
estimates(estimates),
confidence(confidence),
c(c),
gamma(estimates.gamma)
{
nbelem = 0;
foreach_const_it(it, distrib, distrib_type)
nbelem += it->second;
WeibullDistrib m (estimates.beta, estimates.etha, estimates.gamma);
logl_estimates = model_log_likelihood(distrib, nbelem, m);
ntk_assert(confidence <= 0.99996 && confidence >= 0.99994, "");
}
