Detection　of　violent　crowd　behavior　is　an　important　topic　in　crowd　surveillance.　Through　a　study　on　optical　flow,　we　can　find　that　when　crowd　violence　occurs,　the　change　of　variance　on　optical　flow　is　become　large.　Hence,　we　introduce　a　statistic　method　based　on　optical　flow　field　to　detect　violent　crowd　behaviors.　Our　method　considers　the　statistical　characteristics　of　optical　flow　field　and　extracts　a　statistical　characteristic　of　the　optical　flow　(SCOF)　descriptor　from　these　characteristics　to　represent　the　sequences　of　video　frames.　The　SCOF　descriptors　are　then　categorized　as　either　normal　or　violence　using　linear　Support　Vector　Machine.　The　experiments　are　conducted　on　Crowd　Database　and　Hockey　dataset.　Experimental　results　show　the　SCOF　descriptor　is　easy　and　can　efficiently　detect　the　crowd　violence.　©　2014　IEEE.