A coarse-to-fine framework for multiple pedestrian crossing detection

When providing route guidance to pedestrians, one of the major safety considerations is to ensure that streets are crossed at places with pedestrian crossings. As a result, map service providers are keen to gather the location information about pedestrian crossings in the road network. Most, if not all, literature in this field focuses on detecting the pedestrian crossing immediately in front of the camera, while leaving the other pedestrian crossings in the same image undetected. This causes an under-utilization of the information in the video images, because not all pedestrian crossings captured by the camera are detected. In this research, we propose a coarse-to-fine framework to detect pedestrian crossings from probe vehicle videos, which can then be combined with the GPS traces of the corresponding vehicles to determine the exact locations of pedestrian crossings. At the coarse stage of our approach, we identify vanishing points and straight lines associated with the stripes of pedestrian crossings, and partition the edges to obtain rough candidate regions of interest (ROIs). At the fine stage, we determine whether these candidate ROIs are indeed pedestrian crossings by exploring their prior constraint information. Field experiments in Beijing and Shanghai cities show that the proposed approach can produce satisfactory results under a wide variety of situations.

Fan Yuhua, Sun Zhonggui, Zhao Guoying

Publication type:
A1 Journal article – refereed

Place of publication:

coarse-to-fine, detection, pedestrian crossing, probe vehicle video


Full citation:
Fan, Y.; Sun, Z.; Zhao, G. A Coarse-to-Fine Framework for Multiple Pedestrian Crossing Detection. Sensors 2020, 20, 4144, https://doi.org/10.3390/s20154144


Read the publication here: