Redirection Detection Thresholds (RDTs) are defined to represent the limits of undetectable gains and serve as important input parameters for redirected walking algorithms. However, it is not trivial to get a user's RDT estimation in a few trials with existing methods such as the commonly used Method of Constant Stimuli (MCS). In aim to achieve efficient RDT estimation, we chose a classic psychophysical method-the Method of Adjustment (MoA), and compared it against MCS with a series of within-subject experiments respectively on translation, rotation and curvature gains. The results show that MoA gets overall similar RDT estimations with MCS over the same population, except for some systematic differences on translation and rotation gains. Moreover, MoA (with 20 trials) saves about 33% experiment time when compared against MCS, and has the potential to save more as the results of MoA remain relatively stable when the number of trials decreases. Further studies are needed to compare MoA with adaptive methods and to discover the potential relationship between RDTs and perception traits at individual level.