This article formulates and evaluates four different methods for six-degrees-of-freedom binaural reproduction of head-worn microphone array recordings, which may find application within future augmented reality contexts. Three of the explored methods are signalindependent, utilizing least-squares, magnitude least-squares, or plane wave decomposition--based solutions. Rotations and translations are realized by applying directional transformations to the employed spherical rendering or optimization grid. The fourth considered approach is a parametric signal-dependent alternative, which decomposes the array signals into directional and ambient components using beamformers. The directional components are then spatialized by applying binaural filters corresponding to the transformed directions, whereas the ambient sounds are reproduced using the magnitude least-squares solution. Formal perceptual studies were conducted, whereby test participants rated the perceived relative quality of the four binaural rendering methods being evaluated. Of the three signal-independent approaches, the magnitude least-squares solution was rated the highest. The parametric approach was then rated higher than the magnitude least-square solution when the listeners were permitted to move away from the recording point.