Abstract—In this paper, a fusing approach of a 3D sensor and
a camera are used to improve the reliability of pedestrian
detection. The proposed pedestrian detecting system adopts
DBSCAN to cluster 3D points and projects the candidate clusters
onto images as region of interest (ROI). Those ROIs are detected
by HOG (histograms of oriented gradients) pedestrian detector.
Because the DBSCAN groups together 3D points and rejects
outlier points correctly, the proposed system has a low false
detection rate. The performance is also improved since the
proposed system only detects the ROI instead of the whole color
image.