Year: 2024
Type: conference-paper
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.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4403780557