Name
Abstract | ||
|---|---|---|
Human face tracker is one of important research areas that is continuously developing. Many methods have been developed for performing an effective and efficient face tracker based system application. One category of the face tracker methods is the real-time face tracker, which is a challenging task in this field. This paper presents a real-time human face tracker development using facial feature extraction. The skin color method is adopted to obtain the face region because of its efficiency in computing which is required in real time face tracker system. The detection and localization of the face and its features is instrumental for the successful performance of subsequent tasks in related computer vision applications. Many high-level vision applications such as facial feature tracking, facial modeling and animation, facial expression analysis and face recognition require reliable feature extraction system. Face detection system is concerned with finding whether there are any faces in a given image. Facial feature points are referred to in the literature as salient points, anchor points or facial landmarks. The most frequently occurring facial features are the four eye corners, the tip of the nose and the two mouth corners. Facial feature detection is a challenging computer vision problem due to high inter-personal changes such as gender, race and the intra-personal variability such as pose, expression and acquisition conditions like lighting, scale, facial accessories. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICETET.2010.93 | ICETET |
Keywords | Field | DocType |
efficient face tracker,facial accessory,real-time face tracker,real-time human face tracker,face recognition,human face tracker,facial expression analysis,face tracker method,face region,active facial tracking,real time face tracker,pixel,real time,skin,object tracking,computer vision,thresholding,face detection,face,feature extraction | Computer vision,Object detection,Facial recognition system,Face hallucination,Pattern recognition,Three-dimensional face recognition,Computer science,Facial expression,Artificial intelligence,Face detection,Kanade–Lucas–Tomasi feature tracker,Facial motion capture | Conference |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mandalapu Sarada Devi | 1 | 21 | 2.24 |
| Preeti R. Bajaj | 2 | 81 | 14.51 |