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.

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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
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article

Unlimited Vision: Professional Composition by Yourself

Liaoruxing Zhang, Dandan Li, Xin Jin, Longteng Jiang
Digital Storytelling and Education
article

Unlimited Vision: Professional Composition by Yourself

Liaoruxing Zhang, Dandan Li, Xin Jin, Longteng Jiang
article en

Abstract

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.

Xidian University (CN), Beijing Electronic Science and Technology Institute (CN)
Openalex Percentile: Top 70%
Digital Storytelling and Education
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Unlimited Vision: Professional Composition by Yourself — Liaoruxing Zhang, Dandan Li, et al. · (2024) | TGRS Research Map | TGRS