Tracking and analyzing the movement trajectories of individuals and groups is an important problem with applications in crowd management and the development of transportation systems. However, real-world tracking is limited due to the size of the trackable area and the precision with which a person can be tracked. Experiments in virtual environments have many advantages, including practically unlimited sizes and the precise measurement of spatial behavior. However, the generalizability of research using virtual environments to real-world scenarios is often limited by the translation of participants’ movements to those of their avatars. We compared human movement patterns in virtual environments with different control interfaces: a handheld joystick, a mouse-and-keyboard setup, and a keyboard-only setup. With each of these controls, participants completed several movement-related tasks of varying difficulty in a limited amount of time. Questionnaires indicated that participants preferred the mouse-and-keyboard setup over the other two setups. Standard performance measures suggested that the joystick underperformed in a variety of tasks. Movement trajectories in the final task indicated that each of the control setups produced somewhat realistic behavior, despite some apparent differences from real-world trajectories. Overall, the results indicated that, given limited resources, mouse-and-keyboard setups consistently outperform joysticks and produce realistic movement patterns.