Pedestrian Association and Localization in Monocular FIR Video Sequence
Abstract
This paper addresses the frame-to-frame data association and state estimation problems in localization of a pedestrian relative to a moving vehicle from a monocular far infra-red video sequence. Using a novel application of the hierarchical model-based motion estimation framework, we are able to use the image appearance information to solve the frame-to-frame data association problem and estimate a sub-pixel accurate height ratio for a pedestrian in two frames. Then, to localize the pedestrian, we propose a novel approach of using the pedestrian height ratio estimates to guide an interacting multiple-hypothesis-mode/height filtering algorithm instead of using a constant pedestrian height model. Experiments on several IR sequences demonstrate that this approach achieves results comparable to those from a known pedestrian height thus avoiding errors from a constant height model based approach.
Cite
Text
Bansal et al. "Pedestrian Association and Localization in Monocular FIR Video Sequence." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2009. doi:10.1109/CVPRW.2009.5204132Markdown
[Bansal et al. "Pedestrian Association and Localization in Monocular FIR Video Sequence." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2009.](https://mlanthology.org/cvprw/2009/bansal2009cvprw-pedestrian/) doi:10.1109/CVPRW.2009.5204132BibTeX
@inproceedings{bansal2009cvprw-pedestrian,
title = {{Pedestrian Association and Localization in Monocular FIR Video Sequence}},
author = {Bansal, Mayank and Wu, Shunguang and Eledath, Jayan},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2009},
pages = {38-45},
doi = {10.1109/CVPRW.2009.5204132},
url = {https://mlanthology.org/cvprw/2009/bansal2009cvprw-pedestrian/}
}