Most　existing　traffic　camera　calibration　algorithms　work　on　the　basis　of　lane　length,　vehicle　size　prior　information;　however　in　unstructured　road　there　are　often　no　traffic　lanes.　In　order　to　improve　the　applicability　of　camera　calibration　algorithms　in　unstructured　road,　a　dynamic　camera　calibration　algorithm　combining　with　the　camera　linear　model　and　homogeneous　fog　is　presented　in　this　paper;　this　algorithm　only　contains　road　surface　and　moving　vehicles.　Three　main　steps　are　included　in　the　algorithm.　Firstly,　the　algorithm　generate　and　update　scenes　background　and　scene　activity　diagram,　extract　texture　features　of　the　road　and　sky,　search　interesting　region　by　the　area　search　algorithm　(ASA)　and　judge　whether　it　is　homogeneous　fog　or　not　according　to　the　pixel　changing　form　in　the　interesting　region;　Secondly,　calculate　scene　transmittance　for　each　point　in　the　scene　according　to　dark　channel　prior　and　map　it　toto　display　as　an　image.　Finally,　deduce　camera　calibration　equation　by　combining　with　light　transmission　model,　linear　camera　model　and　dark　channel　prior;　select　eight　road　surface　points　with　special　transmittance　on　the　road　surface　to　generate　two　linear　equations,　one　quadratic　equation　and　a　trigonometric　equation　to　calibrate　camera　parameters　in　turn,　get　exact　camera　parameters　value　through　multi-frame　average.　At　the　end　of　this　paper,　calibration　results　are　given.　Comparisons　with　the　conner　detection　method,　six　point　calibration　algorithm　and　calibration　algorithm　based　on　vanishing　point　verify　the　effectiveness　of　this　algorithm;　meanwhile　this　proposed　algorithm　can　satisfy　real　time　video　processing.