3D　face　recognition　has　become　one　of　the　most　active　research　topics　in　face　recognition　due　to　its　robustness　in　the　variation　on　pose　and　illumination.　3D　database　is　the　basis　of　this　work.　Design　and　construction　of　the　face　database　mainly　include　acquisition　of　prototypical　3D　face　data,　preprocessing　and　standardizing　of　the　data　and　the　structure　design.　Currently,　BJUT-3D　database　is　the　largest　Chinese　3D　face　database　in　the　world.　It　contains　1200　Chinese　3D　face　images　and　provides　both　the　texture　and　shape　information　of　human　faces.　This　data　resource　plays　an　important　role　in　3D　face　recognition　and　face　model.　In　this　paper,　the　data　description,　data　collection　schema　and　the　post-processing　methods　are　provided　to　help　using　the　data　and　future　extension.　A　3D　face　data　dense　correspondence　method　is　introduced.　Dense　correspondence　means　that　the　key　facials　points　are　carefully　labeled　and　aligned　among　different　faces,　which　can　be　used　for　a　broad　range　of　face　analysis　tasks.　As　an　application,　a　pose　estimation　and　face　recognition　algorithm　across　different　poses　is　proposed.　Eexpremental　results　show　that　the　proposed　algorithm　has　a　good　performance.