Construction　of　high　resolution　images　from　low　resolution　sequences　having　rigid　or　semi-rigid　objects　with　unified　motions　is　often　important　in　surveillance　and　other　applications.　In　this　paper　a　novel　object-based　super　resolution　reconstruction　scheme　was　proposed,　in　which　a　six-parameter　affine　model-based　object　tracking　and　registration　method　was　first　used　to　segment　and　match　objects　among　a　sequence　of　low　resolution　frames.　The　motion　model　was　then　further　extended　to　the　traditional　maximum　a　posterior　(MAP)　super　resolution　algorithm.　The　proposed　object　tracking　and　registration　method　was　evaluated　by　both　simulated　and　real　acquired　sequences.　The　results　have　demonstrated　the　high　accuracy　of　the　proposed　object　based　method　and　the　enhanced　reconstruction　performance　of　the　extended　approach.