本文整理汇总了C++中eigen::MatrixXf::normalize方法的典型用法代码示例。如果您正苦于以下问题：C++ MatrixXf::normalize方法的具体用法？C++ MatrixXf::normalize怎么用？C++ MatrixXf::normalize使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类eigen::MatrixXf的用法示例。
在下文中一共展示了MatrixXf::normalize方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: acosf
template <typename PointInT, typename GradientT, typename PointOutT> void
pcl::RIFTEstimation<PointInT, GradientT, PointOutT>::computeRIFT (
const PointCloudIn &cloud, const PointCloudGradient &gradient,
int p_idx, float radius, const std::vector<int> &indices,
const std::vector<float> &sqr_distances, Eigen::MatrixXf &rift_descriptor)
{
if (indices.empty ())
{
PCL_ERROR ("[pcl::RIFTEstimation] Null indices points passed!\n");
return;
}
// Determine the number of bins to use based on the size of rift_descriptor
int nr_distance_bins = static_cast<int> (rift_descriptor.rows ());
int nr_gradient_bins = static_cast<int> (rift_descriptor.cols ());
// Get the center point
pcl::Vector3fMapConst p0 = cloud.points[p_idx].getVector3fMap ();
// Compute the RIFT descriptor
rift_descriptor.setZero ();
for (size_t idx = 0; idx < indices.size (); ++idx)
{
// Compute the gradient magnitude and orientation (relative to the center point)
pcl::Vector3fMapConst point = cloud.points[indices[idx]].getVector3fMap ();
Eigen::Map<const Eigen::Vector3f> gradient_vector (& (gradient.points[indices[idx]].gradient[0]));
float gradient_magnitude = gradient_vector.norm ();
float gradient_angle_from_center = acosf (gradient_vector.dot ((point - p0).normalized ()) / gradient_magnitude);
if (!pcl_isfinite (gradient_angle_from_center))
gradient_angle_from_center = 0.0;
// Normalize distance and angle values to: 0.0 <= d,g < nr_distances_bins,nr_gradient_bins
const float eps = std::numeric_limits<float>::epsilon ();
float d = static_cast<float> (nr_distance_bins) * sqrtf (sqr_distances[idx]) / (radius + eps);
float g = static_cast<float> (nr_gradient_bins) * gradient_angle_from_center / (static_cast<float> (M_PI) + eps);
// Compute the bin indices that need to be updated
int d_idx_min = (std::max)(static_cast<int> (ceil (d - 1)), 0);
int d_idx_max = (std::min)(static_cast<int> (floor (d + 1)), nr_distance_bins - 1);
int g_idx_min = static_cast<int> (ceil (g - 1));
int g_idx_max = static_cast<int> (floor (g + 1));
// Update the appropriate bins of the histogram
for (int g_idx = g_idx_min; g_idx <= g_idx_max; ++g_idx)
{
// Because gradient orientation is cyclical, out-of-bounds values must wrap around
int g_idx_wrapped = ((g_idx + nr_gradient_bins) % nr_gradient_bins);
for (int d_idx = d_idx_min; d_idx <= d_idx_max; ++d_idx)
{
// To avoid boundary effects, use linear interpolation when updating each bin
float w = (1.0f - fabsf (d - static_cast<float> (d_idx))) * (1.0f - fabsf (g - static_cast<float> (g_idx)));
rift_descriptor (d_idx, g_idx_wrapped) += w * gradient_magnitude;
}
}
}
// Normalize the RIFT descriptor to unit magnitude
rift_descriptor.normalize ();
}