•Proposed a multidimensional 3D model quality assessment system.•Proposed a five-level evaluation criterion based on 3D model quality index.•Established an UAV multi-angle nap-of-the-object image acquisition (MNIA) framework.•The MNIA framework mitigates 3D model texture distortion and low resolution issues.•Photographing perpendicular to discontinuities enhances 3D model interpretability. The 3D real scene model of high-steep rock slope established based on UAV image provides convenience for non-contact identification and interpretation of rock mass structures. The quality of 3D models directly influences the interpretability of rock mass structures. However, quantitative studies on the relationship between these two aspects are scarce. Therefore, this study investigates the influence of indicators such as photography distance (D), model brightness (l), angle between photography optical axis and the discontinuity to be interpreted (θd), and texture distortion area ratio (tdp), among others, on the interpretability of the 3D models. Furthermore, it delves into the relationships among these indicators and their practical application effects in complex high-steep rock slopes. On this foundation, a novel multi-indicator quality evaluation method for 3D models constructed using UAV photogrammetry is introduced for the first time. This method, based on a composite index model and incorporating empirical approaches, classifies the quality of 3D models into five levels. Guided by the quality evaluation results and taking into account the terrain development and geometric characteristics of discontinuities, a technical framework supporting the acquisition of high-quality 3D models is proposed, known as multi-angle nap-of-the-object image acquisition (MNIA). The research indicates that the 3D models established based on MNIA exhibit significantly reduced texture distortion, leading to a substantial improvement in recognizability, with a goodness rate of 79.98%, far surpassing that of oblique photogrammetry (41.18%). This study provides crucial guidance for obtaining high-quality UAV image in complex terrain environments and holds significant engineering application value in the fine identification and interpretation of rock mass structures on high-steep rock slopes.