A STUDY ON A JOURNEY THROUGH STORIES IN SEQUENTIAL FRAMES

ABSTRACT: This project is aimed at educating machines to narrate visual stories through creating descriptive and coherent text from image sequences. Based on analyzing objects, actions, emotions, and scene changes, the system constructs narrative text reflecting the story in the images. It intends to simulate human storytelling by extracting temporal and contextual relationships among images. Applications are automatic photo album description, digital storytelling, and assistive technology for the visually impaired. By closing the gap between visual perception and language generation, this approach enhances the way machines interpret and describe sophisticated visual experiences. Keywords: Visual Storytelling, Image Sequence Analysis, Narrative Generation, Scene Understanding, Object and Action Recognition, Emotion Detection, Temporal Context Modeling, Multimodal Learning, Assistive Technology, Image-to-Text Synthesis