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Background music not only provides auditory experience for users, but also conveys, guides, and promotes emotions that resonate with visual contents. Studies on how to synthesize background music for different scenes can promote research in many fields, such as human behaviour research. Although considerable effort has been directed toward music synthesis, the synthesis of appropriate music based on scene visual content remains an open problem. In this paper we introduce an interactive background music synthesis algorithm guided by visual content. We leverage a cascading strategy to synthesize background music in two stages: Scene Visual Analysis and Background Music Synthesis. First, seeking a deep learning-based solution, we leverage neural networks to analyze the sentiment of the input scene. Second, real-time background music is synthesized by optimizing a cost function that guides the selection and transition of music clips to maximize the emotion consistency between visual and auditory criteria, and music continuity. In our experiments, we demonstrate the proposed approach can synthesize dynamic background music for different types of scenarios. We also conducted quantitative and qualitative analysis on the synthesized results of multiple example scenes to validate the efficacy of our approach. CCS CONCEPTS • Applied computing → Sound and music computing; • Humancentered computing → Virtual reality.

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