A STUDY ON A JOURNEY THROUGH STORIES IN SEQUENTIAL FRAMES
AUTHORS:
Mentor
Md.Abdul Kalam
Affiliation
Department CSE (AI & ML), ACE Engineering College
DOI: 
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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 StorytellingImage Sequence Analysis Narrative GenerationScene Understanding Object and Action RecognitionEmotion DetectionTemporal Context Modeling Multimodal LearningAssistive Technology Image-to-Text Synthesis
Article Information
PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume Volume 10, Issue 01
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Feb 24 2026
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Rishitha, B. A. J. ,. R. S. ,. K. (2026). A Study on a Journey Through Stories in Sequential Frames. International Journal of Science, Strategic Management and Technology, Volume 10(01). https://doi.org/10.55041/ijsmt.v2i2.138
Rishitha, B. "A Study on a Journey Through Stories in Sequential Frames." International Journal of Science, Strategic Management and Technology, vol. Volume 10, no. 01, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i2.138.
Rishitha, B. "A Study on a Journey Through Stories in Sequential Frames." International Journal of Science, Strategic Management and Technology Volume 10, no. 01 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i2.138.
References
1.Zainy M. Malakan, Saeed Anwar, Ghulam Mubashar Hassan, "Sequential Vision Language as Story: Storytelling Dataset Benchmarking," Conference Paper, 2022.
2.Chris Bryan, Kwan-Liu Ma, "Temporal Summary Images: An Approach to Narrative Visualization via Interactive Annotation Generation and Placement," IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 1, pp. 511-520, 2017.
3.Wei-Ta Chu, Chia-Hsiang Yu, Hsin-Han Wang, "Optimized Storytelling Comics-Based for Image Sequences Temporal," Multimedia Tools and Applications, Springer, 2015.
4.Zainy M. Malakan, Ghulam Mubashar Hassan, Ajmal Mian, "Vision Transformer Based Model for Describing a Set of Images as a Story," Research Paper, 2023.
5.Md Sultan Al Nahian, Tasmia Tasrin, Sagar Gandhi, Ryan Gaines, Brent Harrison, "A Hierarchical Approach for Visual Storytelling Using Image Description," Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2021.
6.Malihe Alikhani, Piyush Sharma, Shengjie Li, Radu Soricut, Matthew Stone, "Visual-Textual Modeling for Coherence," Findings of the Association for Computational Linguistics (ACL), 2020.
7.Linyi Jin, Yukun Zhu, Chen Sun, Kevin Murphy, Li Fei-Fei, Juan Carlos Niebles, "DeepStory: Video Story QA by Deep Embedded Memory Networks," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
8.Peter J. Liu, Mohammad Saleh, Et al., "Generating Wikipedia by Summarizing Long Sequences," International Conference on Learning Representations (ICLR), 2018.
9.Harsh Agrawal, et al., "Don't Just Listen, Use Your Imagination: Leveraging Visual Common Sense for Non-Visual Tasks," Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
2.Chris Bryan, Kwan-Liu Ma, "Temporal Summary Images: An Approach to Narrative Visualization via Interactive Annotation Generation and Placement," IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 1, pp. 511-520, 2017.
3.Wei-Ta Chu, Chia-Hsiang Yu, Hsin-Han Wang, "Optimized Storytelling Comics-Based for Image Sequences Temporal," Multimedia Tools and Applications, Springer, 2015.
4.Zainy M. Malakan, Ghulam Mubashar Hassan, Ajmal Mian, "Vision Transformer Based Model for Describing a Set of Images as a Story," Research Paper, 2023.
5.Md Sultan Al Nahian, Tasmia Tasrin, Sagar Gandhi, Ryan Gaines, Brent Harrison, "A Hierarchical Approach for Visual Storytelling Using Image Description," Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2021.
6.Malihe Alikhani, Piyush Sharma, Shengjie Li, Radu Soricut, Matthew Stone, "Visual-Textual Modeling for Coherence," Findings of the Association for Computational Linguistics (ACL), 2020.
7.Linyi Jin, Yukun Zhu, Chen Sun, Kevin Murphy, Li Fei-Fei, Juan Carlos Niebles, "DeepStory: Video Story QA by Deep Embedded Memory Networks," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
8.Peter J. Liu, Mohammad Saleh, Et al., "Generating Wikipedia by Summarizing Long Sequences," International Conference on Learning Representations (ICLR), 2018.
9.Harsh Agrawal, et al., "Don't Just Listen, Use Your Imagination: Leveraging Visual Common Sense for Non-Visual Tasks," Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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