Cube surface modeling for human detection in crowd
| Autor: | Tao Yang, Jing Li, Fangbing Zhang, Li Zhongzhen, Lisong Wei |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science Detector ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Solid modeling Task (computing) Shadow 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence Cube business Cluster analysis |
| Zdroj: | ICME |
| DOI: | 10.1109/icme.2017.8019311 |
| Popis: | Human detection in dense crowds poses to be a demanding task owing to complex background and serious occlusion. In this paper, we propose a novel real-time and reliable human detection system. We solve the human detection problem by presenting a novel cube surface model captured by a binocular stereo vision camera. We first propose a cube surface model to estimate the 3D background cubes in the surveillance area. We then develop a shadow-free strategy for cube surface model updating. Thereafter, we present a shadow weighted clustering method to efficiently search for human as well as remove false alarms. Ultimately, we have developed a highly robust human detection system, and we carefully evaluate our system in many real challenge indoor and outdoor scenes. Expensive experiments demonstrate our system achieves real-time performance, higher detection rate and lower face alarms in comparison with state-of-the-art human detection methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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