Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Music thumbnailing via structural analysis
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
The feature and spatial covariant kernel: adding implicit spatial constraints to histogram
Proceedings of the 6th ACM international conference on Image and video retrieval
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Repetition detection is a fundamental issue for music thumbnailing and summarization. In this paper, we propose a new feature, called chroma histogram, which enables us to find out repetitive segments from popular songs accurately and quickly. The feature is robust to tempo variation, because sequential information is removed during the process. The low dimensional feature guarantees a very low computational cost, which is proved by theoretic analysis and experimental evaluation. The objective evaluation results demonstrate that our algorithm outperforms previous approaches in terms of both detecting accuracy and efficiency.