Name
Abstract | ||
|---|---|---|
Player detection is an important part in sports video analysis. Over the past few years, several learning based detection methods using various supervised two-class techniques have been presented. Although satisfactory results can be obtained, a lot of manual labor is needed to construct the training set. To overcome this drawback, this letter proposes a player detection method based on one-class SVM (OCSVM) using automatically generated training data. The proposed method is evaluated using several video clips captured fromWorld Cup 2010, and experimental results show that our approach achieves a high detection rate while keeping the training set construction's cost low. Copyright © 2013 The Institute of Electronics, Information and Communication Engineers. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1587/transinf.E96.D.387 | IEICE Transactions |
Keywords | Field | DocType |
SUPPORT | Computer science,Support vector machine,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
96-D | 2 | 17451361 |
Citations | PageRank | References |
2 | 0.40 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuefeng Bai | 1 | 10 | 6.75 |
| Tiejun Zhang | 2 | 10 | 3.21 |
| Chuan-jun Wang | 3 | 6 | 2.95 |
| Ahmed A. Abd El-Latif | 4 | 371 | 36.32 |
| Xiamu Niu | 5 | 754 | 91.72 |