One of the main drawbacks of vision-based control that remains unsolved is the poor dynamic performances caused by the low acquisition frequency of the vision systems and the time latency due to processing. We propose in this paper to face the challenge of designing a high-performance dynamic visual servo control scheme. Two versatile control laws are developed in this paper: a position-based dynamic visual servoing and an image-based dynamic visual servoing. Both control laws are designed to compute the control torques exclusively from a sequential acquisition of regions of interest containing the visual features to achieve an accurate trajectory tracking. The presented experiments on vision-based dynamic control of a high-speed parallel robot show that the proposed control schemes can perform better than joint-based computed torque control.