Fringe projection profilometry (FPP) is one of the most widely used optical three-dimensional (3-D) perceiving techniques. However, when applied to cluttered scenes, acquiring accurate 3-D shapes is difficult because of the influences of indirect light caused by non-diffuse surfaces. In this paper, we first theoretically analyze and model the influences of indirect light in FPP, and then propose a scene-adaptive pattern coding-based method, which can design projection patterns based on the reflective properties of the scene's surfaces, to achieve accurate 3-D perceiving in cluttered scenes. Specifically, the scene confidence analysis method is first proposed to identify the reflective properties of various surfaces and localize the camera pixels of the diffuse surface. The illumination status (i.e., "0" or "1") of each projector pixel can be determined according to the camera-projection coordinate mapping and spatial pattern coding, where only diffuse surfaces can be illuminated, thus fundamentally preventing the influences of indirect light from the point of view of the light source. The 3-D shapes of diffuse surfaces can be accurately reconstructed in cluttered scenes. Different from traditional reflective properties change or light separation solutions, the proposed method can achieve accurate 3-D perceiving of cluttered scenes without additional hardware or expensive calculation. Extensive experiments verify that the proposed method outperforms the traditional methods in terms of accuracy and robustness.