This paper describes a vehicle guidance strategy for waypoint tracking as well as collision avoidance with unforeseen obstacles using a 2D passive vision sensor mounted on the vehicle. An extended Kalman filter is applied to estimate the position of each obstacle relative to the vehicle from image-based measurements. A collision cone approach is utilized to determine a critical obstacle, and an aiming point for the critical obstacle is set on a boundary of the cone. A minimum-effort guidance law for multiple targets tracking is applied to guide the vehicle to a given waypoint via the aiming point to avoid the critical obstacle. Simulation results illustrate that the suggested minimum-effort guidance achieves a waypoint tracking mission while avoiding obstacles with less control effort when compared to a previously developed sequential proportional navigation approach. Moreover, minimum-effort guidance improves convergence of vision-based obstacle position estimation, and hence enhances obstacle avoidance performance.