@inproceedings{4124704722ee45daa5a0facf5cb76064,
title = "Pedestrian detection using labeled depth data",
abstract = "This paper presents pedestrian detection algorithm on labeled depth data which is obtained from road scenes. Our approach computes feature responses for head and legs of human body using depth and label data. And then, it detects pedestrians by removing edges and partitioning a bipartite graph of head and leg response blobs using prior knowledge about human body. In the experiments, the proposed algorithm produces better result compared to the method which uses histogram of gradient feature and the ground plane for road scenes.",
keywords = "depth data, pedestrian detection, road scene",
author = "Won, {Kwang Hee} and Sisay Gurmu and Jung, {Soon Ki}",
year = "2013",
doi = "10.1109/FCV.2013.6485472",
language = "English",
isbn = "9781467356206",
series = "FCV 2013 - Proceedings of the 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision",
pages = "117--120",
booktitle = "FCV 2013 - Proceedings of the 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision",
note = "19th Korea-Japan Joint Workshop on Frontiers of Computer Vision, FCV 2013 ; Conference date: 30-01-2013 Through 01-02-2013",
}