Intelligent Video Semantic Extraction for Film and Television Music Teaching

As science and technology advance rapidly, video semantic understanding (VSU) technology has made significant strides. This technology has garnered widespread recognition within the music industry and piqued the interest of film and television music creators. In the realm of film music creation, VSU technology serves as a powerful tool, revolutionizing traditional approaches and steering the evolution of film and television music creation. This study employs the Spatiotemporal Pattern-based Saliency Map Generation (SMGTSM) algorithm, which generates saliency maps for each frame in an average of 45.91ms. This is notably faster than methods based on the optical flow field algorithm (81.49ms) and the random sample consensus (RANSAC) algorithm. The application of VSU technology not only enhances traditional film and television music creation methods but also significantly boosts the efficiency and quality of the creative process.