Unlimited Vision: Professional Composition by Yourself
This paper introduces a novel method for enhancing image composition guidance in photography. It utilizes advanced composition rules to guide a Real-Time Detection Transformer (RT-DETR) model in predicting aesthetically pleasing compositions for photographs. Unlike traditional methods constrained by original image boundaries, our approach allows the predicted framing to extend beyond these limits, offering dynamic, real-time guidance for image composition in photography. The system integrates multi-label composition classification and compositional element annotation, using YOLOv8 for key object detection and an enhanced Deep Hough Transform for compositional lines to guide photographers. It provides photographers with real-time guidance for optimal camera adjustments, transforming traditional post-processing tasks into an intuitive, interactive process. This method significantly enhances photographers' flexibility and effectiveness in capturing visually superior photographs.
Authors
- Liaoruxing Zhang (ORCID: https://orcid.org/0009-0009-3341-4342)
- Dandan Li (ORCID: https://orcid.org/0009-0009-1822-5770)
- Xin Jin (ORCID: https://orcid.org/0000-0003-3873-1653)
- Longteng Jiang (ORCID: https://orcid.org/0009-0007-5434-9573)
Institutions
- Xidian University (CN)
- Beijing Electronic Science and Technology Institute (CN)
Publication Details
- Published
- 2024-10-26
- DOI
- https://doi.org/10.1145/3664647.3685001
- Primary Topic
- Digital Storytelling and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00