Mixed Gaussian Model Based Video Foreground Object Detection
| Title | Mixed Gaussian Model Based Video Foreground Object Detection |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Zhang, Caixia, Liu, Xiaoxiao, Xu, Qingyang |
| Conference Name | Proceedings of the 2Nd International Conference on Computer Science and Application Engineering |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-6512-3 |
| Keywords | Human Behavior, Metrics, Mixed Gaussian model, object detection, Object separation, pubcrawl, Resiliency, video surveillance |
| Abstract | Video1 surveillance has been applied to various industries and business, but the video surveillance is mainly to provide video capture and display services at current, and does not care about video content. In some applications, users want to be able to monitor the video content and implement automatic prompting and alarming functions. Therefore, this paper uses the hybrid Gaussian model (GMM) to achieve the separation of the foreground and the background of the video and the experiments validate the effectiveness of the algorithm. |
| URL | https://dl.acm.org/citation.cfm?doid=3207677.3278023 |
| DOI | 10.1145/3207677.3278023 |
| Citation Key | zhangMixedGaussianModel2018 |