Nowadays,　orthodontics　has　become　an　important　part　of　modern　personal　life　to　assist　one　in　improving　mastication　and　raising　self-esteem.　However,　the　quality　of　orthodontic　treatment　still　heavily　relies　on　the　empirical　evaluation　of　experienced　doctors,　which　lacks　quantitative　assessment　and　requires　patients　to　visit　clinics　frequently　for　in-person　examination.　To　resolve　the　aforementioned　problem,　we　propose　a　novel　and　practical　mobile　device-based　framework　for　precisely　measuring　tooth　movement　in　treatment,　so　as　to　simplify　and　strengthen　the　traditional　tooth　monitoring　process.　To　this　end,　we　formulate　the　tooth　movement　monitoring　task　as　a　multi-view　multi-object　pose　estimation　problem　via　different　views　that　capture　multiple　texture-less　and　severely　occluded　objects　(i.e.　teeth).　Specifically,　we　exploit　a　pre-scanned　3D　tooth　model　and　a　sparse　set　of　multi-view　tooth　images　as　inputs　for　our　proposed　tooth　monitoring　framework.　After　extracting　tooth　contours　and　localizing　the　initial　camera　pose　of　each　view　from　the　initial　configuration,　we　propose　a　joint　pose　estimation　scheme　to　precisely　estimate　the　3D　pose　of　each　individual　tooth,　so　as　to　infer　their　relative　offsets　during　treatment.　Furthermore,　we　introduce　the　metric　of　Relative　Pose　Bias　to　evaluate　the　individual　tooth　pose　accuracy　in　a　small　scale.　We　demonstrate　that　our　approach　is　capable　of　reaching　high　accuracy　and　efficiency　as　practical　orthodontic　treatment　monitoring　requires.　©　1995-2012　IEEE.