2020/07/29 by Daniel Yang, TJ Tsai, Yang, Daniel +1
Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Information Retrieval (cs.IR) #Music and Audio Processing #Video Analysis and Summarization #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2007.14579
openalex publication_date 2020/07/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper presents a method for large-scale retrieval of piano sheet music images. Our work differs from previous studies on sheet music retrieval in two ways. First, we investigate the problem at a much larger scale than previous studies, using all solo piano sheet music images in the entire IMSLP dataset as a searchable database. Second, we use cell phone images of sheet music as our input queries, which lends itself to a practical, user-facing application. We show that a previously proposed fingerprinting method for sheet music retrieval is far too slow for a real-time application, and we diagnose its shortcomings. We propose a novel hashing scheme called dynamic n-gram fingerprinting that significantly reduces runtime while simultaneously boosting retrieval accuracy. In experiments on IMSLP data, our proposed method achieves a mean reciprocal rank of 0.85 and an average runtime of 0.98 seconds per query.