The　face,　an　important　part　of　the　body,　conveys　a　lot　of　information.　When　a　driver　is　in　a　state　of　fatigue,　the　facial　expressions,　e.g.,　the　frequency　of　blinking　and　yawning,　are　different　from　those　in　the　normal　state.　In　this　paper,　we　propose　a　system　called　DriCare,　which　detects　the　drivers＇　fatigue　status,　such　as　yawning,　blinking,　and　duration　of　eye　closure,　using　video　images,　without　equipping　their　bodies　with　devices.　Owing　to　the　shortcomings　of　previous　algorithms,　we　introduce　a　new　face-tracking　algorithm　to　improve　the　tracking　accuracy.　Further,　we　designed　a　new　detection　method　for　facial　regions　based　on　68　key　points.　Then　we　use　these　facial　regions　to　evaluate　the　drivers＇　state.　By　combining　the　features　of　the　eyes　and　mouth,　DriCare　can　alert　the　driver　using　a　fatigue　warning.　The　experimental　results　showed　that　DriCare　achieved　around　92%　accuracy.