In　this　paper,　an　effective　birth　intensity　estimation　method　that　based　on　entropy　distribution　and　coverage　rate　is　proposed　for　multi-target　video　tracking.　The　birth　intensity　is　first　initialized　according　to　the　previously　obtained　target　states　and　measurements.　The　currently　obtained　measurements　are　then　used　to　update　the　initialized　birth　intensity.　In　the　updating　stage,　the　negative　exponent　entropy　distribution　that　depends　on　the　weight　is　first　selected　as　the　prior　distribution　of　the　birth　intensity.　By　doing　so,　the　components　within　the　birth　intensity　those　are　irrelevant　to　the　measurements　could　be　regarded　as　noises　and　should　be　removed.　The　coverage　rate　between　each　birth　intensity　component　and　the　corresponding　measurement　is　then　computed　to　further　eliminate　those　components　whose　weights　are　smaller　than　the　given　threshold.　Experiments　on　noisy　video　sequences　are　conducted　to　show　that　the　proposed　birth　intensity　estimation　method　can　effectively　eliminate　the　noises　and　finally　improve　the　tracking　accuracy.　©,　2014,　Institute　of　Computing　Technology.　All　right　reserved.