Building　information　model　(BIM)　needs　to　be　updated　based　on　the　real　situation　on　the　construction　site　to　reflect　the　dynamic　aspects　of　construction　progress.　However,　without　realizing　real-time　tracking　technology　and　semantic　enhancement　for　the　3D　reconstructed　model,　it　is　difficult　to　achieve　an　updating　based　on　the　comparison　of　the　as-designed　BIM　with　the　as-built　BIM　for　any　discrepancy　in　terms　of　quality　and　quantity.　Moreover,　semantic　information　is　usually　missing　in　the　re-constructed　models;　therefore,　it　is　difficult　to　automate　the　process　of　identifying　target　building　components　in　a　complicated　construction　site.　The　present　paper　proposes　an　image-based　3D　reconstruction　while　integrating　infrared　thermography　to　extract　the　semantic　information　from　the　images　as　the　different　emissivity　of　the　construction　materials　is　a　piece　of　crucial　evidence　for　the　identification　of　the　material.　Case　studies　are　conducted　in　an　under　passage　in　a　university　campus　to　investigate　the　feasibility　of　the　proposed　methods.　An　efficient　and　cost-benefit　approach　of　as-built　BIM　updating　is　attainable　considering　the　future　possibility　of　high-level　semantic　information　reasoning　from　different　data　sources.　The　results　of　the　proposed　methodology　show　that　the　thermal　images　perform　better　in　capturing　the　MEP　data　comparing　to　the　3D　reconstruction　using　images　where　MEP　data　are　missing　and　incomplete　in　the　point　cloud.　However,　the　limitations　of　the　methodology,　such　as　the　inconsistent　thermal　conditions　and　the　unpredictable　thermal　radiation　source　will　influence　the　accuracy　of　segmentation　results.　©　2020　American　Society　of　Civil　Engineers.