Head motion during Computed Tomographic (CT) brain imaging studies can adversely affect the reconstructed image through distortion, loss of resolution and other related artifacts. In this paper, we propose a marker based innovative approach to detect and mitigate motion artifacts in three dimensional cone-beam brain CT systems without using any external motion tracking sensor. Motion is detected using correlations between the adjacent projections. Once motion is detected, motion parameters ( i.e. six degrees-of-freedom of motions) are estimated using a numerical optimization technique. Artifacts, caused by motions, are mitigated by using a modified form Feldkemp-Davis-Kress (FDK) algorithm which uses the estimated motion parameters in back-projection stage. The proposed approach has been evaluated on a modified three-dimensional Shepp-Logan phantom with a range of simulated motions. Simulation results demonstrate a quantitative and qualitative validation of motion detection and artifacts mitigation technique.