The　paper　realizes　the　face　detection　algorithm　based　on　the　combination　of　the　skin　model　and　the　Haar　algorithm.　Firstly,　a　platform　for　sample　labeling　was　constructed,　which　combines　the　contour　extraction　algorithm　with　manual　labeling.　By　labeling　more　than　10000　images　obtained　randomly　from　the　Internet,　a　large　training　dataset　is　available.　Then,　a　skin　histogram,　a　non-skin　histogram　and　a　statistical　skin　model　are　constructed　by　analyzing　the　distribution　of　the　skin　and　the　non-skin　color　on　the　basis　of　a　large　training　dataset.　Based　on　this　statistical　color　model,　the　skin　area　is　detected　and　split　from　video　files　frame　by　frame.　With　the　Haar　Object　Detection　algorithm　and　the　morphology　algorithm　such　as　erosion　and　dilation,　the　background　noise　and　non-face　areas　are　removed　from　the　detected　skin　area　and　facial　area　is　detected,　which　provides　the　basis　for　face　recognition　and　the　video-based　visual　speech　synthesis.　Compared　with　the　Haar-based　face　detection　method,　our　algorithm　greatly　improves　the　rate　of　correct　detection　and　reduces　the　rate　of　the　false　positives.　©　(2012)　Trans　Tech　Publications,　Switzerland.