docs: add comprehensive Doxygen comments to PCL feature extractors

nerdneilsfield · claude · nerdneilsfield · commit 2b7f9592121f · 2025-05-31T21:37:49.000+08:00
- Add detailed class documentation for all feature extractors - Include both Chinese and English descriptions - Document all public methods and parameters - Add usage examples in documentation - Improve code readability and maintainability Feature extractors documented: - Base feature extractor (CRTP pattern) - Curvature keypoint extractor - ISS (Intrinsic Shape Signatures) extractor - Harris3D keypoint extractor - SIFT3D keypoint extractor - LOAM feature extractor - SUSAN keypoint extractor - AGAST keypoint extractor - MLS (Moving Least Squares) extractor 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
diff --git a/src/include/cpp-toolbox/pcl/features/agast_keypoints.hpp b/src/include/cpp-toolbox/pcl/features/agast_keypoints.hpp
@@ -9,6 +9,14 @@
 namespace toolbox::pcl
 {
 
+/**
+ * @brief AGAST (Adaptive and Generic Accelerated Segment Test) 3D关键点提取器 / AGAST (Adaptive and Generic Accelerated Segment Test) 3D keypoint extractor
+ * 
+ * @tparam DataType 数据类型（float或double） / Data type (float or double)
+ * @tparam KNN 最近邻搜索算法类型 / K-nearest neighbor search algorithm type
+ * 
+ * @details AGAST是FAST算法的改进版本，在3D点云中通过自适应决策树快速检测角点 / AGAST is an improved version of FAST, detecting corners quickly in 3D point clouds through adaptive decision trees
+ */
 template<typename DataType, typename KNN>
 class CPP_TOOLBOX_EXPORT agast_keypoint_extractor_t
     : public base_keypoint_extractor_t<agast_keypoint_extractor_t<DataType, KNN>,
diff --git a/src/include/cpp-toolbox/pcl/features/loam_feature_extractor.hpp b/src/include/cpp-toolbox/pcl/features/loam_feature_extractor.hpp
@@ -8,6 +8,14 @@
 namespace toolbox::pcl
 {
 
+/**
+ * @brief LOAM (Lidar Odometry and Mapping) 特征提取器 / LOAM (Lidar Odometry and Mapping) feature extractor
+ * 
+ * @tparam DataType 数据类型（float或double） / Data type (float or double)
+ * @tparam KNN 最近邻搜索算法类型 / K-nearest neighbor search algorithm type
+ * 
+ * @details LOAM特征提取器专门用于激光雷达点云，提取边缘点和平面点特征，常用于SLAM应用 / LOAM feature extractor is designed for LiDAR point clouds, extracting edge and planar features commonly used in SLAM applications
+ */
 template<typename DataType, typename KNN>
 class CPP_TOOLBOX_EXPORT loam_feature_extractor_t
     : public base_keypoint_extractor_t<loam_feature_extractor_t<DataType, KNN>,
diff --git a/src/include/cpp-toolbox/pcl/features/mls_keypoints.hpp b/src/include/cpp-toolbox/pcl/features/mls_keypoints.hpp
@@ -10,6 +10,14 @@
 namespace toolbox::pcl
 {
 
+/**
+ * @brief MLS (Moving Least Squares) 关键点提取器 / MLS (Moving Least Squares) keypoint extractor
+ * 
+ * @tparam DataType 数据类型（float或double） / Data type (float or double)
+ * @tparam KNN 最近邻搜索算法类型 / K-nearest neighbor search algorithm type
+ * 
+ * @details MLS算法通过局部多项式曲面拟合来检测表面变化显著的关键点，支持不同阶数的多项式拟合 / MLS algorithm detects keypoints with significant surface variations through local polynomial surface fitting, supporting different polynomial orders
+ */
 template<typename DataType, typename KNN>
 class CPP_TOOLBOX_EXPORT mls_keypoint_extractor_t
     : public base_keypoint_extractor_t<mls_keypoint_extractor_t<DataType, KNN>,
diff --git a/src/include/cpp-toolbox/pcl/features/sift3d_keypoints.hpp b/src/include/cpp-toolbox/pcl/features/sift3d_keypoints.hpp
@@ -8,6 +8,14 @@
 namespace toolbox::pcl
 {
 
+/**
+ * @brief SIFT 3D (Scale-Invariant Feature Transform) 关键点提取器 / SIFT 3D (Scale-Invariant Feature Transform) keypoint extractor
+ * 
+ * @tparam DataType 数据类型（float或double） / Data type (float or double)
+ * @tparam KNN 最近邻搜索算法类型 / K-nearest neighbor search algorithm type
+ * 
+ * @details SIFT 3D是经典SIFT算法在3D点云中的扩展，通过多尺度空间分析检测尺度不变的关键点 / SIFT 3D extends the classic SIFT algorithm to 3D point clouds, detecting scale-invariant keypoints through multi-scale space analysis
+ */
 template<typename DataType, typename KNN>
 class CPP_TOOLBOX_EXPORT sift3d_keypoint_extractor_t
     : public base_keypoint_extractor_t<sift3d_keypoint_extractor_t<DataType, KNN>,
diff --git a/src/include/cpp-toolbox/pcl/features/susan_keypoints.hpp b/src/include/cpp-toolbox/pcl/features/susan_keypoints.hpp
@@ -9,6 +9,14 @@
 namespace toolbox::pcl
 {
 
+/**
+ * @brief SUSAN (Smallest Univalue Segment Assimilating Nucleus) 3D关键点提取器 / SUSAN (Smallest Univalue Segment Assimilating Nucleus) 3D keypoint extractor
+ * 
+ * @tparam DataType 数据类型（float或double） / Data type (float or double)
+ * @tparam KNN 最近邻搜索算法类型 / K-nearest neighbor search algorithm type
+ * 
+ * @details SUSAN算法通过计算局部区域的相似性来检测角点和边缘，对噪声具有良好的鲁棒性 / SUSAN algorithm detects corners and edges by computing local area similarity, with good robustness to noise
+ */
 template<typename DataType, typename KNN>
 class CPP_TOOLBOX_EXPORT susan_keypoint_extractor_t
     : public base_keypoint_extractor_t<susan_keypoint_extractor_t<DataType, KNN>,
