
This paper presents an approach for pedestrian detection in the nighttime driving with a normal camera. Bright objects in the video are extracted with an adaptive thresholding segmentation algorithm. Then, the size, position, and shape of each object are analyzed to judge whether it is a pedestrian. A tracking module is used to verify the result at last. Experimental results show that the proposed method can detect 71.26% pedestrians.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
