This thesis focused on understanding how humans visually perceive swarm behavior through the use of swarm simulations and gaze tracking. The goal of this project was to determine visual patterns subjects display while observing and supervising a swarm as well as determine what swarm characteristics affect these patterns. As an ultimate goal, it was hoped that this research will contribute to optimizing human-swarm interaction for the design of human supervisory controllers for swarms. To achieve the stated goals, two investigations were conducted. First, subjects gaze was tracked while observing a simulated swarm as it moved across the screen. This swarm changed in size, disturbance level in the position of the agents, speed, and path curvature. Second, subjects were asked to play a supervisory role as they watched a swarm move across the screen toward targets. The subjects determined whether a collision would occur and with which target while their responses as well as their gaze was tracked. In the case of an observatory role, a model of human gaze was created. This was embodied in a second order model similar to that of a spring-mass-damper system. This model was similar across subjects and stable. In the case of a supervisory role, inherent weaknesses in human perception were found, such as the inability to predict future position of curved paths. These findings are discussed in depth within the thesis. Overall, the results presented suggest that understanding human perception of swarms offers a new approach to the problem of swarm control. The ability to adapt controls to the strengths and weaknesses could lead to great strides in the reduction of operators in the control of one UAV, resulting in a move towards one man operation of a swarm.