Humanoid robots have been used in a wide range of applications including entertainment, healthcare, and assistive living. In these applications, the robots are expected to perform a range of natural body motions, which can be either preprogrammed or learnt from human demonstration. This paper proposes a strategy for imitating dynamic walking gait for a humanoid robot by formulating the problem as an optimization process. The human motion data are recorded with an inertial sensor-based motion tracking system (Biomotion+). Joint angle trajectories are obtained from the transformation of the estimated posture. Key locomotion frames corresponding to gait events are chosen from the trajectories. Due to differences in joint structures of the human and robot, the joint angles at these frames need to be optimized to satisfy the physical constraints of the robot while preserving robot stability. Interpolation among the optimized angles is needed to generate continuous angle trajectories. The method is validated using a NAO humanoid robot, with results demonstrating the effectiveness of the proposed strategy for dynamic walking.