This　paper　presents　a　novel　3D　reconstruction　method　through　incorporating　passive　vision　method　based　on　shape　from　shading　and　active　vision　method　based　on　visible　space,　which　aims　at　the　automatic　measurement　and　reconstruction　of　unknown　three　dimensional　objects.　Firstly,　the　images　of　unknown　object　at　initial　position　and　the　position　rotating　180　degrees　from　the　initial　position　are　obtained　using　a　CCD　camera.　To　obtain　the　rough　model　of　the　unknown　object,　an　improved　Tsai-SFS　algorithm　is　adopted　to　recover　the　object　shape　according　to　the　prior　obtained　images.　And　then　through　incorporating　the　visible　space　models　of　the　monocular　line-laser　active　vision　system　along　Z　axis　rotation　and　X　axis　flip　directions,　the　unknown　region　of　the　object　is　predicted.　Finally,　according　to　the　visibility　of　the　next　viewpoint,　the　view　planning　process　is　divided　into　an　object　surface　reconstruction　planning　and　an　upper　surface　reconstruction　planning.　And　the　location　that　can　obtain　maximum　visual　surface　area　and　optimal　reconstruction　precision　is　defined　as　the　next　best　view　point.　Real　object　was　reconstructed　in　experiment　to　validate　the　feasibility　and　efficiency　of　the　proposed　method.