Abstract: Dense granular-liquid two-phase flows are ubiquitous in natural phenomena such as debris flows and landslides, as well as in industrial processes including deep-sea mining and thickening operations. Numerous researchers have employed laboratory-scale open-channel inclined chute experiments to investigate the flow characteristics and rheological properties of these complex flows. However, restricted by the opacity of granular-liquid systems, previous studies were often limited to observing the flow behavior at the sidewalls, at the free surface, or at the basal layer, making it difficult to obtain a statistical information regarding the internal granular phase. To address the critical challenge of measuring internal flow fields in dense granular-liquid two-phase flows caused by their opacity, this study designed and constructed an experimental system integrating optical visualization with a mechanical measurement. Based on Refractive Index Matching (RIM) technology and combined with the Planar Laser-Induced Fluorescence (PLIF) method, the system achieves the optical transparency of the granular flow medium. Particle Tracking Velocimetry (PTV) is employed to capture the kinematic information of the granular phase in the core flow region non-intrusively and with high spatiotemporal resolution. This paper elaborates on the overall design of the experimental system, on its key components (including the inclined chute and feeding system, the RIM-PLIF system, and the opto-electronic synchronization system), and on the experimental data processing algorithms (a PTV framework combining Hough transform identification and nearest-neighbor matching tracking). Finally, through a typical case study of a dense granular-liquid mixture flowing down an inclined chute, the feasibility of the system in acquiring the complex internal flow information—including velocity profiles, area fraction profiles, shear rates, and granular temperature profiles—is successfully validated. This work provides a novel research avenue and a comprehensive dataset for investigating the rheological constitutive relations of granular materials at the particle scale.