Estimating Gaze Directions for Pedestrian Navigation

ZHOU Sha; NIU Jiqiang; XU Feng; PAN Xiaofang; ZHEN Wenjie; QIAN Haoyue

doi:10.13203/j.whugis20200465

Volume 46 Issue 5

May 2021

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Geomatics and Information Science of Wuhan University > 2021 > 46(5): 700-705,735. > DOI: 10.13203/j.whugis20200465

ZHOU Sha, NIU Jiqiang, XU Feng, PAN Xiaofang, ZHEN Wenjie, QIAN Haoyue. Estimating Gaze Directions for Pedestrian Navigation[J]. Geomatics and Information Science of Wuhan University, 2021, 46(5): 700-705,735. DOI: 10.13203/j.whugis20200465

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Estimating Gaze Directions for Pedestrian Navigation

ZHOU Sha^{1, 2, 3,},
NIU Jiqiang^{1, 2, 3, ,},
XU Feng^{1, 2, 3},
PAN Xiaofang^{1, 2, 3},
ZHEN Wenjie⁴,
QIAN Haoyue⁴

1.
School of Geographic Science, Xinyang Normal University, Xinyang 464000, China
2.
Henan Engineering Research Center for Remote Sensing Big Data and Intelligent Analysis of Huaihe River Basin, Xinyang 464000, China
3.
Henan Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, Xinyang 464000, China
4.
School of Geography and Information Engineering, China University of Geosciences(Wuhan), Wuhan 430000, China

Funds:

The National Natural Science Foundation of China 41771438

The National Natural Science Foundation of China 41671405

The National Natural Science Foundation of China 41701449

The National Natural Science Foundation of China 41701446

The National Natural Science Foundation of China 41971356

the Science and Technology Planning Project of Henan Province 212102310027

the Key Scientific Research Projects for Higher Education of Henan Province 19A170012

the Natural Science Foundation of Henan Province 202300410345

the Postgraduate Education Reform and Quality Improvement Project of Henan Province HNYJS2020JD14

the Nanhu Scholars Program for Young Scholars of Xinyang Normal University

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Author Bio:
ZHOU Sha, PhD, lecturer, specializes in pedestrian navigation and place descriptions.E-mail: zhousha@xynu.edu.cn
Corresponding author:
NIU Jiqiang, PhD, professor. E-mail: niujiqiang@xynu.edu.cn
Received Date: August 31, 2020
Published Date: May 04, 2021

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Abstract

Abstract

Objectives Accurately capturing gaze directions of pedestrians can effectively improve the efficiency and the safety of pedestrian navigation. Traditional methods of gaze direction estimation are somewhat invasive in many practical applications and unadapted to different users and head pose variations, and unsuitable for pedestrian navigation in terms of the portability of the corresponding devices. Accordingly, we propose a model to estimate the gaze directions of pedestrians using smart glasses.
Methods Based on scale invariant feature transform features, we first measure the similarity degree between gaze photos and street view images. Then we propose a method to estimate gaze directions while pedestrians and street view images are disjoint.When pedestrians and street view images are overlapped, we develop another estimation method that considers the position error of pedestrians. Furthermore, we establish a gaze-direction estimation model that considers the positional relationship between pedestrians and street view images. Finally, we select two real-world scenes to verify the reliability of the proposed estimation model of gaze directions by simulation experiments.Results: The results show that: (1) The estimation errors of the gaze directions by simulation experiments.
Results The results show that: (1) The estimation errors of the proposed estimation model(i.e., gaze-direction estimation model considering positional relationship) are significantly lower than that of gaze-directions estimation model ignoring positional relationship. (2) In the same scenes, the estimated error does not increase with the test distances. Moreover, the average estimation accuracy of our model is almost similar to the estimation method based on depth cameras.
Conclusions (1) The proposed gaze direction estimation is significantly superior to the model that ignores positional relationship.(2) Pedestrian position variations have little impact on the estimation accuracies of our model in the same scene. Hence, the proposed model is suitable for pedestrian navigation and we can use portable smart glasses to estimate gaze directions.
- pedestrian navigation,
- gaze directions estimation,
- gaze photo,
- street view,
- image similarity

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References (21)

References

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