In this paper, we present motion retargeting and control algorithms for teleoperated physical human-robot interaction (pHRI). We employ unilateral teleoperation in which a sensor-equipped operator interacts with a static object such as a mannequin to provide the motion and force references. The controller takes the references as well as current robot states and contact forces as input, and outputs the joint torques to track the operator's contact forces while preserving the expression and style of the motion. We develop a hierarchical optimization scheme combined with a motion retargeting algorithm that resolves the discrepancy between the contact states of the operator and robot due to different kinematic parameters and body shapes. We demonstrate the controller performance on a dual-arm robot with soft skin and contact force sensors using pre-recorded human demonstrations of hugging.