Print Email Facebook Twitter Analysing the performance of the OLAF framework in the context of identifying music in movies Title Analysing the performance of the OLAF framework in the context of identifying music in movies Author Hildebrand, Casper (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Intelligent Systems) Contributor Liem, C.C.S. (mentor) Kim, Jaehun (mentor) Krijthe, J.H. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2021-07-02 Abstract This paper presents the findings of a benchmark performed on the audio fingerprinting framework OLAF in the context of movie music. The goal is to find a music identification framework suitable for automatically identifying a song from a movie clip. This research aims to find how well OLAF performs in this context with regard to the criteria determined in the benchmark and to see if the performance can be increased. The OLAF framework makes use of parameters, which are individually tweaked and benchmarked with synthesised data. These findings are then combined to find a set of parameters that is used to perform this same benchmark on real clips from movies. The found parameter setup slightly increased the performance, going from 1 true positive and 133 false negatives in the original setup to 5 true positives, 3 false positives and 126 false negatives. Subject audio fingerprintingmusicmovies To reference this document use: http://resolver.tudelft.nl/uuid:ea13cb1d-6498-45f4-a58c-060578709ee7 Part of collection Student theses Document type bachelor thesis Rights © 2021 Casper Hildebrand Files PDF OLAF.pdf 561.92 KB Close viewer /islandora/object/uuid:ea13cb1d-6498-45f4-a58c-060578709ee7/datastream/OBJ/view