Name
Title | ||
|---|---|---|
Robust nose detection and tracking using gentleboost and improved Lucas-Kanade optical flow algorithms |
Abstract | ||
|---|---|---|
The problem of face feature points detection is an important research topic in many fields such as face image analysis and human-machine interface. In this paper, we propose a robust method of 2D nose detection and tracking system. This system can be valuable for disabled people or for cases where hands are busy with other tasks. The required information is derived from video data captured with an inexpensive web camera. Position of the nose tip is determined with the use of a Gabor wavelet feature based GentleBoost detector. Once the nose tip is initially located, an improved Lucas-Kanade optical flow method is used to track the nose tip feature point. Experiments show that our system is able to process 18 frames per second at a resolution of 320×240 pixels. This method will in future be used in a non-contact interface for disabled users. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74171-8_126 | ICIC (1) |
Keywords | Field | DocType |
improved lucas-kanade optical flow,disabled people,nose tip,human-machine interface,disabled user,nose tip feature point,robust method,nose detection,robust nose detection,face image analysis,non-contact interface,face feature points detection,human machine interface,lucas kanade,gabor wavelets,optical flow,frames per second,tracking system,image analysis,data capture | Computer vision,Pattern recognition,Computer science,Gabor wavelet,Tracking system,Nose,Pixel,Artificial intelligence,Frame rate,Lucas–Kanade method,Optical flow,Detector | Conference |
Volume | ISSN | ISBN |
4681 | 0302-9743 | 3-540-74170-4 |
Citations | PageRank | References |
5 | 0.50 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaobo Ren | 1 | 102 | 11.14 |
| Jiatao Song | 2 | 49 | 7.36 |
| Hongwei Ying | 3 | 6 | 1.21 |
| Yani Zhu | 4 | 9 | 1.63 |
| Xuena Qiu | 5 | 15 | 2.88 |