Open AccessAn Improved Visual Background Extraction Algorithm Combining Depth Information
Author(s) -
Feng Yang,
Jiang Sheng,
Wenwu Ye
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1229/1/012019
Subject(s) - pixel , computer science , background subtraction , artificial intelligence , algorithm , computer vision , frame (networking) , sensitivity (control systems) , channel (broadcasting) , image (mathematics) , engineering , telecommunications , computer network , electronic engineering
ViBe is one of the most commonly used background subtraction method, which conducts foreground detection on each frame pixel-by-pixel. When the algorithm is applied to video sequence with large depth differences such as forest fire surveillance, the problem of traditional ViBe is appearing. If the algorithm parameters of different depth are the same, it will inevitably lead to two situations: the nearby shaking of trees is easy to cause false detection because of the large pixel area, and the distant smoke is easy to miss as it occupies small pixels of the image. To solve this problem, an improved visual background extraction algorithm combining depth information is proposed. The method calculates the dark channel information as depth information, and a conversion function is designed to adjust sensitivity to accommodate moving targets with huge depth difference. The experimental results demonstrate that the improved ViBe algorithm has better performance than traditional ViBe algorithm in forest fire surveillance. In addition, the improvement of the algorithm does not excessively increase the computational time-consuming.