RETRACTED: Moving object surveillance using object proposals and background prior prediction
| Autor: | Yiyang Yao, Luming Zhang, Peizhen Liu, Xiaowei Sun |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Binary number 020207 software engineering 02 engineering and technology Time cost Object detection Constant false alarm rate Norm (mathematics) Signal Processing 0202 electrical engineering electronic engineering information engineering Media Technology 020201 artificial intelligence & image processing Computer vision Computer Vision and Pattern Recognition Artificial intelligence Electrical and Electronic Engineering Detection rate business |
| Zdroj: | Journal of Visual Communication and Image Representation. 61:85-92 |
| ISSN: | 1047-3203 |
| DOI: | 10.1016/j.jvcir.2019.03.006 |
| Popis: | In this paper, a moving object detection algorithm is combined with a background estimate and a Bing (Binary Norm Gradient) object is proposed in video surveillance. A simple background estimation method is used to detect rough images of a group of moving foreground objects. The foreground setting in the foreground will estimate another set of candidate object windows, and the target (pedestrian/vehicle) from the intersection area comes from the first two steps. In addition, the time cost is reduced by the estimated area. Experiments on outdoor datasets show that the proposed method can not only achieve high detection rate (DR), but also reduce false alarm rate (FAR) and time cost. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect