Digital Video Technology and Image Detection Algorithms in Film and Television Post-Production

With the advent of the information age, a large amount of digital information is flooding human's daily life and people can easily access it. Due to the massive use of smartphones, tablets and other mobile devices, digital video has become a mainstream multimedia application and is widely used in various fields such as video teaching, video conferencing, video-on-demand, entertainment and social networking, news and judicial criminal investigation. Digital video has become an important medium for the daily transmission of information. The main objective of this paper is to investigate the application of digital video technology and image detection algorithms in film and television post-production. This paper first introduces scene boundary detection, analyses the reasons why existing sampling strategies still suffer from the loss of optimal foreground and background pixel pairs; investigates fuzzy multi-criteria foreground and background pixel pair evaluation methods, proposes an infrared pedestrian classification algorithm based on fully automatic keying enhancement, and finally conducts experiments on video scene boundary detection and analyses the results. The experimental results show that the method proposed in this paper performs relatively better in terms of detection rate and accuracy compared with the method using only lens visual features, although its recall and accuracy rate are still somewhat lower compared to a movie with a smoother video pace.