This　paper　is　dedicated　to　address　the　limitations　of　vision-based　displacement　monitoring　(VDM)　methods　when　monitoring　multiple　targets.　It　first　introduces　a　two-dimensional　(2D)　VDM　method　for　automated　monitoring　of　multiple　target　displacements,　eliminating　the　need　for　manual　template　selection　and　repeated　camera　calibration.　The　method　uses　coded　artificial　targets　supplemented　by　intelligent　algorithms　and　self-calibration　techniques.　A　three-dimensional　(3D)　VDM　method　is　then　developed　for　displacement　monitoring　using　two　independent　cameras.　The　efficacy　and　precision　of　the　proposed　methods　were　extensively　validated　through　numerical　simulations　and　experimental　studies.　The　numerical　simulation　results　show　that　coded　targets　can　be　accurately　detected　and　identified.　Shaker　test　results　show　that　the　proposed　2D　VDM　method　effectively　monitors　multiple　encoded　targets　in　different　planes　and　autonomously　complete　the　whole　process.　The　proposed　3D　VDM　method　accurately　monitors　the　3D　displacements　of　multiple　targets　on　a　bridge　using　only　two　independent　cameras.