研究目的
To develop an interactive system for synthesizing images based on user sketches, addressing the challenges of retrieving relevant images from daily scenes and seamlessly composing them.
研究成果
MindCamera is an effective system for interactive image synthesis, providing high retrieval precision and natural compositing results, with potential for further improvements in accuracy and efficiency.
研究不足
The contour extraction algorithm may have sub-optimal results for images with multiple objects, and image tags from YOLO are not always accurate, which could affect semantics incorporation.
1:Experimental Design and Method Selection:
The system uses a sketch-based scene image retrieval model with contour extraction, feature representation using GF-HOG, and similarity measures. For image synthesis, it employs GrabCut with Poisson image editing or alpha matting for seamless blending.
2:Sample Selection and Data Sources:
The dataset includes complex daily scenes from Microsoft COCO validation dataset (40,000 images) and Flickr 160 dataset for evaluation.
3:List of Experimental Equipment and Materials:
No specific equipment mentioned; software-based methods are used.
4:Experimental Procedures and Operational Workflow:
Users draw a sketch; the system retrieves images, segments objects using GrabCut or alpha matting, and blends them into backgrounds.
5:Data Analysis Methods:
Precision@K curves are used to evaluate retrieval performance, and average synthesis time is measured.
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