Name
Abstract | ||
|---|---|---|
Face detection is an important step in many video applications. Several algorithms have been proposed to this task, but most of them do not consider the spatio-temporal information. In this paper two recently introduced spatio-temporal descriptors are analyzed and evaluated in the context of face detection in videos. We designed and tested two full face detectors on the challenging YouTube Faces database. The obtained results are compared with those obtained by a frame-by-frame approach with a spatial descriptor, showing that using spatio-temporal descriptors can boost the detection performance. |
Year | Venue | Keywords |
|---|---|---|
2014 | PROGRESS IN PATTERN RECOGNITION IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2014 | face detection, spatio-temporal representation, video |
Field | DocType | Volume |
Computer vision,Object-class detection,Pattern recognition,Computer science,Video tracking,Artificial intelligence,Face detection,Detector | Conference | 8827 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yoanna Martínez-Díaz | 1 | 30 | 7.48 |
| Noslen Hernández | 2 | 7 | 4.57 |
| Heydi Méndez-Vázquez | 3 | 47 | 12.91 |