Dual Approach for Video Summarization: Key Frame Captioning and Audio Summarization

With the rapid growth of video content, finding efficient ways to summarize videos has become increasingly important for quickly understanding their key messages. This paper focuses on developing a dual visual-auditory-based approach to video summarization. Captions based on key frames will take the most prominent visual elements of a video and transform them into short captions for easy and quick acquisition of essential visual information. Audio summarization uses speech-to-text transcription and reads out the content to summarize it into a brief copy, thereby making an audio copy easily accessible. This process separates the visual and audio parts for processing so that video content is summarized more fully yet efficiently. Technologies include OpenCV and BLIP for visual summarization, Whisper and LLaMa for transcribing and summarizing the audio. Such techniques collectively allow for the making of clear and concise video summaries that help users quickly understand what is visualized as well as said in videos.