Analysis method of rural industry revitalization film and television materials based on multimedia data feature extraction technology

Abstract

Systematically and efficiently accessing film and television materials concerning rural industrial revitalization is an issue of great interest today. From traditional text-based retrieval methods for multimedia data to contemporary methods that apply feature extraction technologies for multimedia content, there has been considerable improvement in retrieval rates and precision. This research aims to refine the essentials of the content-based video retrieval phase, establish a high-precision video retrieval system, and promote effective access to film and television resources that aid in revitalizing rural industries. An innovative calculation technique for shot boundary detection is introduced, incorporating both adaptive high- and low-threshold approaches. This method demonstrates a 3.2% enhancement in precision rates for films focused on rural industry revitalization and an 8.5% improvement for documentaries compared to conventional methodologies. The technique independently evaluates abrupt and gradual shot transitions, implementing a secondary evaluation mechanism to reduce the effects of atypical conditions on detection accuracy. The advanced keyframe extraction algorithm, utilizing K-means clustering, shows higher precision. According to evaluations conducted by testers, the accuracy rate of the proposed technique is 85%, compared to 70% for conventional methods. By applying advanced feature extraction technologies, this study extracts the intrinsic essence of multimedia materials to form substantive content related to rural revitalization. In this way, it enhances access for rural populations by fostering innovation in industrial structures and supporting the sustainable development of rural industries.