Name
Abstract | ||
|---|---|---|
In this paper, we propose a method for calculating the dynamic background region in a video and removing false positives in order to overcome the problems of false positives that occur due to the dynamic background and frame drop at slow speeds. Therefore, we need an efficient algorithm with a robust performance value including processing speed. The foreground is separated from the background by comparing the similarities between false positives and the foreground. In order to improve the processing speed, the median filter was optimized for the binary image. The proposed method was based on a CDnet 2012/2014 dataset and we achieved precision of 76.68%, FPR of 0.90%, FNR of 18.02%, and an F-measure of 75.35%. The average ranking across categories is 14.36, which is superior to the background subtraction method. The proposed method was operated at 45 fps (CPU), 150 fps (GPU) at 320 × 240 resolution. Therefore, we expect that the proposed method can be applied to current commercialized CCTV without any hardware upgrades. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Computer Vision and Pattern Recognition | Background subtraction,Pattern recognition,Motion detection,Computer science,Artificial intelligence,Region analysis,False positive paradox |
DocType | Volume | Citations |
Journal | abs/1805.09277 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sang-Ha Lee | 1 | 0 | 0.34 |
| Soon-Chul Kwon | 2 | 9 | 2.63 |
| Jin-Wook Shim | 3 | 0 | 0.34 |
| Jeong Eun Lim | 4 | 0 | 0.34 |
| Jisang Yoo | 5 | 9 | 3.64 |