Being　able　to　locate　a　specified　people　and　to　simultaneously　follow　him　in　an　unknown　environment　has　become　an　essential　capability　of　service　robots.　Lots　of　efficient　methods　for　implementing　this　so-called　people　tracking　and　following　capability　have　been　proposed.　However,　these　mature　methods　cannot　be　applied　for　civil　use　readily　for　their　high　cost.　The　appearance　of　low-cost　RGB-D　camera　solves　this　problem　and　there　have　been　sorts　of　methods　describing　how　to　build　a　people　tracking　and　following　module　with　RGB-D　camera.　For　the　sake　of　cost　control,　the　modules　based　on　low-cost　RGB-D　camera　always　suffer　from　noise,　low-range　and　low-precision　problem.　We　present　a　method　that　implements　people　tracking　and　following　based　on　RGB-D　data　generated　by　Microsoft　Kinect　sensor,　in　indoor　environment.　Furthermore,　we　also　discuss　a　set　of　methods　to　optimize　the　result　in　order　to　filter　the　noise,　extend　the　detected　range　and　decreasing　the　effect　of　low-precision.