Comix – A Deep Learning Approach to Automated Educational Comic Creation
Effective child education necessitates innovative and captivating methods. In this paper, we present Comix, a system that uses deep learning to turn videos into child-friendly comic strips. Video processing, feature extraction, keyframe selection via temporal and aesthetic analysis, cartoon-style transformation, speech-to-text conversion, and text placement within comic panels are all steps in Comix’s multi-stage pipeline. Comix transforms complex video content into an engaging and easily assimilated comic format by fusing simplified narratives with visual storytelling driven by deep learning. Our results show that, while preserving the main idea of the original material, the system greatly improves accessibility, engagement, and comprehension among children. This study demonstrates how deep learning has the potential to completely transform the way that educational content is delivered by offering a scalable method for turning video-based information into visually captivating comic narratives.
Authors
- Rujuta Kulkarni
- Dhananjay Bhagat (ORCID: https://orcid.org/0009-0009-1100-3219)
- Ayush Patil
- Ravija Pasalkar
- Ananya Salunkhe
Institutions
- MIT World Peace University (IN)
Publication Details
- Published
- 2025-07-25
- DOI
- https://doi.org/10.1109/isac364032.2025.11156259
- Primary Topic
- Educational Games and Gamification
- Type
- article
- Field-Weighted Citation Impact
- 0.00