This　paper　proposed　a　robust　framework　of　detecting　the　real-time　queuing　and　dissipation　of　a　vehicle　queue　by　two　cameras,　one　fixed　at　the　front　of　the　stop　line　and　the　other　somewhere　behind　the　stop　line,　jointly　monitoring　the　interested　region　with　opposite　and　long-range　views.　Firstly,　the　position　changes　of　the　tail　and　head　of　a　vehicle　queue,　which　accurately　describe　the　formation　and　dissipation　of　the　queue,　can　be　efficiently　tracked　in　each　camera　at　intersection　during　morning　and　evening　rush　hours,　with　a　duplex　flexible　window　fused　with　the　Haar　feature　based　AdaBoost　cascade　classifiers.　Secondly,　the　data　of　these　two　cameras　in　this　large-area　outdoor　traffic　application　are　fused　at　decision　level　to　improve　the　accuracy　of　the　tracking,　according　to　the　tracking　result　in　each　camera.　Then,　the　queue　length　and　stop　delay　of　vehicles　can　be　calculated　readily.　Experiments　show　that　the　proposed　method　can　detect　the　formation　and　dissipation　of　the　queue　under　varying　illumination　in　real　time,　and　that　the　accuracy　rate　is　about　90.24%.　Therefore,　this　method　can　be　further　applied　to　traffic　congestion　monitoring　and　traffic　signal　controlling.