Abstract A key component of Mars exploration is the operation of robotic instruments on the surface, such as those on board the Mars Exploration Rovers, the Mars Science Laboratory (MSL), and the planned Mars 2020 Rover. As the instruments carried by these rovers have become more advanced, the area targeted by some instruments becomes smaller, revealing more fifine-grained details about the geology and chemistry of rocks on the surface. However, thermal flfluctuations, rover settling or slipping, and inherent inaccuracies in pointing mechanisms all lead to pointing error that is on the order of the target size (several millimeters) or larger. We show that given a target located on a previously acquired image, the rover can align this with a new image to visually locate the target and refifine the current pointing. Due to round-trip communication constraints, this visual targeting must be done effifi- ciently on board the rover using relatively limited computing hardware. We employ existing ORB features for landmark-based image registration, describe and theoretically justify a novel approach to fifiltering false landmark matches, and employ a random forest classififier to automatically reject failed alignments. We demonstrate the effificacy of our approach using over 3,800 images acquired by Remote Micro-Imager on board the “Curiosity” rover