In　the　class　of　not-contact　sensors,　the　techniques　of　vision-based　displacement　estimation　enable　one　to　gather　dense　global　measurements　of　static　deformation　as　well　as　of　dynamic　response.　They　are　becoming　more　and　more　available　thanks　to　the　ongoing　technology　developments.　In　this　work,　a　vision　system,　which　takes　advantage　of　fast-developing　digital　image　processing　and　computer　vision　technologies　and　provides　high　sample　rate,　is　implemented　to　monitor　the　2D　plane　vibrations　of　a　reduced　scale　frame　mounted　on　a　shaking　table　as　available　in　a　laboratory.　The　physical　meanings　of　the　camera　parameters,　the　trade-off　between　the　system　resolution　and　the　field-of-view,　and　the　upper　limitation　of　marker　density　are　discussed.　The　scale　factor　approach,　which　is　widely　used　to　convert　the　image　coordinates　measured　by　a　vision　system　in　the　unit　of　pixels　into　space　coordinates,　causes　a　poor　repeatability　of　the　experiment,　an　unstable　experiment　precision,　and　therefore　a　global　poor　flexibility.　To　overcome　these　problems,　two　calibrations　approaches　are　introduced:　registration　and　direct　linear　transformation.　Based　on　the　constructed　vision-based　displacement　measurement　system,　several　experiments　are　carried　out　to　monitor　the　motion　of　a　scale-reduced　model　on　which　dense　markers　are　glued.　The　experiment　results　show　that　the　proposed　system　can　capture　and　successfully　measure　the　motion　of　the　laboratory　model　within　the　required　frequency　band.　©　2013　Elsevier　Ltd.