With　the　traditional　Gaussian　mixture　model　being　more　sensitive　to　light　and　failing　to　react　to　changes　of　lighting,　a　variances　and　a　mean　update　program　under　local　illumination　and　global　illumination　mutations　are　puts　forward　respectively　in　this　paper.　More　specifically,　a　divergent　method　to　update　the　mean　of　each　Gaussian　distribution　in　the　background　model　is　proposed,　following　the　analyses　of　the　average　grey　value　of　current　image　frame　and　the　absolute　difference　of　the　average　grey　value　of　the　background　model.　An　innovative　update　method　to　update　the　variance　of　Gaussian　mixture　model　is　also　presented,　based　on　the　study　of　the　absolute　value　of　the　pixel　value　and　mean　value.　Experimental　results　show　that　the　algorithm　can　not　only　detect　moving　targets　in　a　relatively　more　complete　manner,　but　also　exhibits　better　adaptability　and　robustness　for　outdoor　lighting　mutation.