Accurate　maps　play　a　vital　role　in　the　localization　of　mobile　robots　and　autonomous　vehicles.　However,　the　traditional　methods　of　creating　precise　maps　of　scenes　involve　special　probe　vehicles　equipped　with　expensive　devices,　making　the　generalization　and　commercialization　of　accurate　mapping　difficult.　This　paper　proposes　a　novel　method　to　generate　accurate　sparse　landmarks　maps　of　the　environment　using　a　general　commercial　stereo　camera　in　a　multi-session　pattern.　It　consists　of　a　visual　SLAM　frontend　for　obtaining　individual　session　maps　and　a　backend　for　performing　overlap　detection　and　multi-session　joint　optimization.　Experiments　on　the　KITTI　datasets　validate　the　proposed　method.　It　demonstrates　that　the　proposed　method　can　generate　an　accurate　map　only　using　a　low-precision　and　low-cost　stereo　camera.　Its　accuracy　is　even　on　par　with　that　of　3D　LiDAR-based　LOAM.　©　2021　IEEE