Name
Abstract | ||
|---|---|---|
Human tracking is an important function to an automatic surveillance system using a vision sensor. Human face is one of the most significant features to detect person(s) in an image. However, face is not always observed from a single camera. Therefore, it is difficult to identify a person exactly in an image due to the variety of poses. This paper describes a method for automatic human tracking based on the face detection using Haar-like features and the mean shift tracking method. Additionally, the method increases its trackability by using multi-viewpoint images. The validity of the proposed method is shown through experiment. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ROBIO.2011.6181528 | Robotics and Biomimetics |
Keywords | DocType | ISBN |
Haar transforms,cameras,face recognition,feature extraction,image sensors,object detection,object tracking,pose estimation,surveillance,Haar-like features,automatic human tracking method,automatic surveillance system,face detection,mean shift tracking method,most significant features,multiple cameras,multiviewpoint images,person detection,person identification,vision sensor | Conference | 978-1-4577-2136-6 |
Citations | PageRank | References |
4 | 0.47 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Atsushi Yamashita | 1 | 321 | 67.29 |
| Ito, Y. | 2 | 54 | 6.22 |
| Toru Kaneko | 3 | 5 | 1.52 |
| Hajime Asama | 4 | 130 | 7.34 |