Name
Abstract | ||
|---|---|---|
In this paper, a new spatio-temporal saliency model is presented. Based on the idea that both spatial and temporal features are needed to determine the saliency of a video, this model builds upon the fact that locally contrasted and globally rare features are salient. The features used in the model are both spatial (color and orientations) and temporal (motion amplitude and direction) at several scales. To be more robust to moving camera a module computes the global motion and to be more consistent in time, the saliency maps are combined together after a temporal filtering. The model is evaluated on a dataset of 24 videos split into 5 categories (Abnormal, Surveillance, Crowds, Moving camera, and Noisy). This model achieves better performance when compared to several state-of-the-art saliency models. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICIP.2013.6738712 | 2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013) |
Keywords | Field | DocType |
Visual attention, Saliency, Rarity Mechanism, Optical Flow | Crowds,Computer vision,Kadir–Brady saliency detector,Pattern recognition,Salience (neuroscience),Computer science,Filter (signal processing),Feature extraction,Video tracking,Artificial intelligence,Filtering theory,Salient | Conference |
ISSN | Citations | PageRank |
1522-4880 | 8 | 0.52 |
References | Authors | |
10 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| marc decombas ab | 1 | 14 | 2.03 |
| Nicolas Riche | 2 | 184 | 9.75 |
| Frédéric Dufaux | 3 | 462 | 57.88 |
| Béatrice Pesquet-Popescu | 4 | 876 | 91.43 |
| Matei Mancas | 5 | 315 | 27.50 |
| Bernard Gosselin | 6 | 198 | 12.88 |
| Thierry Dutoit | 7 | 1006 | 123.84 |