Object　tracking　is　always　in　the　core　status　with　the　develop　of　robotics.　In　this　paper,　we　proposed　a　novel　tracking　framework　based　on　Spatio-Temporal　Context　tracking　(STC)　and　Template-Matching　algorithm(TM).　STC　tracking　method　is　a　fast　and　simplified　tracking　method　that　strongly　dependent　on　the　context　region　(the　surrounding　background　of　the　target).　Therefore,　it　cannot　correct　the　tracking　error　by　itself　and　even　lost　the　target　during　tracking.　Under　this　circumstance,　we　make　a　closed-loop　judgment　whether　the　movement　of　the　target　between　two　neighboring　image　sequence　larger　than　a　constant　or　not.　If　the　movement　larger　than　the　constant,　the　template　matching　is　employed　as　sample　detector　to　correct　the　error　or　re-track　the　target　on　line.　The　templatematching　algorithm　is　an　efficient　and　fast　detection　algorithm　that　find　the　maximum　probability　point　in　the　image　that　similar　to　the　template.　In　order　to　decrease　the　calculating　time,　the　search　region　is　not　the　whole　image　but　the　context　region　of　STC　tracking　method.　What＇s　more,　after　tracking　and　detecting　we　update　the　scale　parameter　to　adapt　the　change　of　the　target＇s　appearance.　Finally,　experimental　result　demonstrate　that　our　tracking　method　have　improve　the　robustness　of　tracking.