Pedestrian's Gaze Object Detection in Traffic Scene

Hiroto Murakami, Jialei Chen, Daisuke Deguchi, Takatsugu Hirayama, Takatsugu Hirayama, Yasutomo Kawanishi, Yasutomo Kawanishi, Hiroshi Murase

2024

Abstract

In this paper, we present a new task of detecting an object that a target pedestrian is gazing at in a traffic scene called PEdestrian’s Gaze Object (PEGO). We argue that the detection of gaze object can provide important information for pedestrian’s behavior prediction and can contribute to the realization of automated vehicles. For this task, we construct a dataset of in-vehicle camera images with annotations of the objects that pedestrians are gazing at. Also, we propose a Transformer-based method called PEGO Transformer to solve the PEGO detection task. The PEGO Transformer directly performs gaze object detection with the utilization of whole-body features without a high-resolution head image and a gaze heatmap which the traditional methods rely on. Experimental results showed that the proposed method could estimate pedestrian’s gaze object accurately even if various objects exist in the scene.

Paper Citation

in Harvard Style

Murakami H., Chen J., Deguchi D., Hirayama T., Kawanishi Y. and Murase H. (2024). Pedestrian's Gaze Object Detection in Traffic Scene. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 333-340. DOI: 10.5220/0012309500003660

in Bibtex Style

@conference{visapp24,
author={Hiroto Murakami and Jialei Chen and Daisuke Deguchi and Takatsugu Hirayama and Yasutomo Kawanishi and Hiroshi Murase},
title={Pedestrian's Gaze Object Detection in Traffic Scene},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2024},
pages={333-340},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012309500003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - Pedestrian's Gaze Object Detection in Traffic Scene
SN - 978-989-758-679-8
AU - Murakami H.
AU - Chen J.
AU - Deguchi D.
AU - Hirayama T.
AU - Kawanishi Y.
AU - Murase H.
PY - 2024
SP - 333
EP - 340
DO - 10.5220/0012309500003660
PB - SciTePress