Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
407012 | Neurocomputing | 2014 | 14 Pages |
Abstract
In recent years, extensive research efforts have been dedicated to automatic news content analysis. In this paper, we propose a novel algorithm for anchorperson detection in news video sequences. In this method, the raw news videos are firstly split into shots by a four-threshold method, and the key frames are extracted from each shot. After that, the anchorperson detection is conducted from these key frames by using a clustering-based method based on a statistical distance of Pearson's correlation coefficient. To evaluate the effectiveness of the proposed method, we have conducted experiments on 10 news sequences. In these experiments, the proposed scheme achieves a recall of 0.96 and a precision of 0.97 for anchorperson detection.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Ping Ji, Liujuan Cao, Xiguang Zhang, Longfei Zhang, Weimin Wu,