Is it possible using photographs as source (e.g., selfies of users) to affect and enhance mood, emotion and creativity by creating AI based “digital painters” that can create art painting output that is deemed to convey a certain mood from any source photograph (user face portraits, dancers in moment)? The goal of this research is to use our Creative Artificial Intelligence System (CAIS) along with our cognitive based painting algorithms (DiPaola 2013) together with additional art analysis tools (i.e., texture and palette synthesis) to parameterize a generative artistic painting process based on mood and emotion. We discuss our methods and begin to validate the work by performing two intertwined user studies that appear to support that viewers of the generated art from our CAIS agree to a high degree on a specific mood the output conveys from our 4 emotional spaces regardless of the source material: abstract, fugitive or their self portrait. This points to the conclusion that our CAIS system can automatically generate unique artworks or “aesthetic visualization” that deemed creative and have emotional qualities, which has benefits and repeatability in many interactive fields. This work has User Experience (UX) applications in computational creativity, affective aesthetic visualization, experiential learning (of art), performance visualization (dancing), and health well-being.