The traffic generated by video streaming applications constitutes a large portion of the Internet traffic carried over today's networks. Video streaming demands low latency and high bandwidth. In particular, the transmission of high-quality (high-resolution) streaming video may put the network under pressure. Therefore, high-quality video traffic requires network managers to implement smart and fast routing decisions. Software Defined Networking (SDN) provides a global view and centralized control for the whole network which gives opportunities to dynamically manage networks. In this paper, we use an OpenFlow-based SDN environment and propose a dynamic routing scheme with online traffic estimation to increase the quality of high-quality video streaming and the throughput of the network. The traffic is clustered using an unsupervised machine learning algorithm, high-quality video flows are identified and routed over less congested paths. The whole design is tested in the Mininet simulator. Simulation results show that the proposed scheme improves the link utilization and reduces the amount of dropped frames as a result of excessive delay.