<![CDATA[Cinematic visual aspects such as lighting, color, and camera framing play an important role in shaping emotional and narrative experiences in 3D animation. However, their translation into measurable computational emotional outputs remains limited. This study proposes a computational framework for modeling audience emotional perception in a static 3D animated environment by integrating visual hermeneutics, quantitative analysis, and fuzzy logic inference. A total of 450 animation frames from a single 3D interior setting were analyzed across three narrative phases: beginning, climax, and resolution. Qualitative shot-by-shot analysis was used to interpret the symbolic function of visual elements, while quantitative data were obtained from light intensity and color temperature measurements and an emotional perception questionnaire analyzed using repeated measures ANOVA. The results show significant differences in depression, tension, and hope across narrative phases (p < 0.001), corresponding to systematic changes in lighting, color, and framing. The study formalizes cinematic visual parameters as fuzzy input variables and produces a measurable emotional index through defuzzification, consistent with the ANOVA findings. The novelty of this study lies in integrating visual hermeneutics and fuzzy logic to model emotion in a static 3D environment and validate it statistically. Practically, the model can support animators and multimedia designers in planning emotion-oriented lighting strategies and evaluating visual scenes more systematically.]]>
