From 0a2415061360e17384885b6d7cc7b61b1bdd3065 Mon Sep 17 00:00:00 2001 From: "k.koide" Date: Fri, 9 Aug 2024 10:54:06 +0900 Subject: [PATCH] use CC and url commands --- docs/paper.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/docs/paper.md b/docs/paper.md index 5c694db..e4811fd 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -16,6 +16,8 @@ date: 22 June 2024 bibliography: paper.bib --- +\def\CC{{C\nolinebreak[4]\hspace{-.05em}\raisebox{.4ex}{\tiny\bf ++}}} + # Summary Point cloud registration is a task of aligning two point clouds measured by 3D ranging @@ -34,7 +36,7 @@ processing, speed is a critical factor in point cloud registration routines. fast point cloud registration pipeline. It offers parallel implementations of downsampling, nearest neighbor search, local feature extraction, and registration to accelerate the entire process. -small_gicp is implemented as a header-only C++ library with minimal dependencies +small_gicp is implemented as a header-only \CC library with minimal dependencies to offer efficiency, portability, and customizability. # Statement of need @@ -73,10 +75,10 @@ we designed small_gicp with the following features: offering up to 2x speed gain in single-threaded scenarios and better scalability in multi-core environments. -- A modular and customizable framework using C++ templates, allowing easy customization of the +- A modular and customizable framework using \CC templates, allowing easy customization of the algorithm's internal workings while maintaining efficiency. -- A header-only C++ library implementation for easy integration into user projects, with Python bindings +- A header-only \CC library implementation for easy integration into user projects, with Python bindings provided for collaborative use with other libraries (e.g., Open3D). # Functionalities @@ -107,7 +109,7 @@ distribution-to-distribution correspondence). - Multi-threaded construction of `small_gicp::KdTree` can be up to 6x faster than that of `nanoflann`. - Single-threaded `small_gicp::GICP` is about 2.4x faster than `pcl::GICP`, with the multi-threaded version showing better scalability. -More details can be found at https://github.com/koide3/small_gicp/blob/master/BENCHMARK.md. +More details can be found at \url{https://github.com/koide3/small_gicp/blob/master/BENCHMARK.md}. # Future work