Scaled physical experiments allow us to directly observe deformational processes that take place on time and length scales that are impossible to observe in the Earth's crust. Successful evaluation of advection and uplift of material within a restraining bend along a strike-slip fault zone depends on capturing the evolution of strain in three dimensions. Consequently, we require deformation within the horizontal plane as well as vertical motions. While 3D digital image correlation systems can provide this information, their high costs have prompted us to develop techniques that require only two DSLR cameras and a few Matlab (R) toolboxes, which are available to researchers at many institutions. Matlab (R) plug-ins can perform particle image velocimetry (PIV), a technique used in many analog modeling studies to map the incremental displacements fields. For tracking material advection throughout experiments more suitable Matlab (R) plug-ins perform particle tracking velocimetry (PTV), which tracks the complete two-dimensional displacement path of individual particles. To capture uplift the Matlab (R) Computer Vision Toolbox (TM), uses pairs of photos to capture the evolving topography of the experiment. The stereovision approach eliminates the need to stop the experiment to perform 3D laser scans, which can be problematic when working with materials that have time dependent rheology. We demonstrate how the combination of PIV, PTV, and stereovision analysis of experiments that simulate the Mount McKinley restraining bend reveal the evolution of the fault system and three-dimensional advection of material through the bend.