Three-dimensional　(3D)　model　acquisition　is　the　process　of　building　a　3D　model　of　an　object.　But　due　to　the　limited　field　of　view　of　the　scanner,　this　task　is　mainly　performed　by　taking　several　scans　with　human　intervention.　In　order　to　make　the　3D　modeling　process　efficient,　a　novel　automatic　3D　modeling　method　for　unknown　objects　based　on　hybrid　vision　technology　in　a　binocular　structured　light　system　(BSLS)　is　proposed.　Firstly,　the　limit　visual　vacuums　of　the　BSLS　are　established,　and　they　will　be　used　to　predict　the　unknown　area　with　an　acquired　2.5D　range　image.　With　the　2D　intensity　image　acquired　synchronously,　the　coarse　boundary　size　is　recovered　from　Shape　from　Shading,　and　it　leads　the　prediction　of　the　unknown　area　to　be　more　precise.　Based　on　the　combination　of　the　predicted　contours,　the　next　best　viewpoint　is　determined　with　more　unknown　areas　visible.　The　proposed　method　can　be　used　to　obtain　the　3D　models　of　unknown　objects　automatically,　and　the　experimental　results　illustrate　the　validity　and　efficiency　of　our　approach.　©　2017,　Korean　Society　for　Precision　Engineering　and　Springer-Verlag　Berlin　Heidelberg.