Zhang, J.Q. and Zhang, H.Y. (2017). Clustering by Fast Search and Find of Density Peaks Based on Manifold Distance. Computer Knowledge & Technology, 13, 179-182.

has been cited by the following article:

• TITLE: A Clustering Algorithm for Key Frame Extraction Based on Density Peak

  AUTHORS: Hong Zhao, Tao Wang, Xiangyan Zeng

  KEYWORDS: Key Frame, Clustering Algorithm, HSV Color Histogram

  JOURNAL NAME: Journal of Computer and Communications, Vol.6 No.12, December 26, 2018

  ABSTRACT: Aiming at the problem of video key frame extraction, a density peak clustering algorithm is proposed, which uses the HSV histogram to transform high-dimensional abstract video image data into quantifiable low-dimensional data, and reduces the computational complexity while capturing image features. On this basis, the density peak clustering algorithm is used to cluster these low-dimensional data and find the cluster centers. Combining the clustering results, the final key frames are obtained. A large number of key frame extraction experiments for different types of videos show that the algorithm can extract different number of key frames by combining video content, overcome the shortcoming of traditional key frame extraction algorithm which can only extract a fixed number of key frames, and the extracted key frames can represent the main content of video accurately.