Name
Abstract | ||
|---|---|---|
Estimating the initial background of a scene is a key prerequisite for several applications in video analytics. In this paper, we present a simple approach that takes into account spatio-temporal motion intensities while estimating the true background. We tested the algorithm on real video sequences from the Scene Background Initialization (SBI) benchmark dataset, and the results show that the algorithm is competitive compared to the state of the art. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/AVSS.2017.8078485 | 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) |
Keywords | Field | DocType |
spatio-temporal motion estimation,video analytics,account spatio-temporal motion intensities,video sequences,scene background initialization benchmark dataset,SBI | Computer vision,Pattern recognition,Computer science,Artificial intelligence,Initialization,Motion estimation,Cluster analysis,Artificial neural network,Analytics | Conference |
ISBN | Citations | PageRank |
978-1-5386-2940-6 | 0 | 0.34 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sriram Varadarajan | 1 | 0 | 0.68 |
| hui wang | 2 | 76 | 17.01 |
| Bryan W. Scotney | 3 | 670 | 82.50 |
| Omar Nibouche | 4 | 89 | 13.50 |