Ms. Jingmin Xi Profile

Jingmin Xi

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 1 August 2023 Paper

An adaptive inherent bias correction strategy embedded with spatio-temporal attention network for pedestrian trajectory prediction

Jingmin Xi, Jie Chen, Zhixiang Huang, Yingjian Deng, Bin Li, Haitao Wang

Proceedings Volume 12754, 127541H (2023) https://doi.org/10.1117/12.2684205

KEYWORDS: Bias correction, Deep learning

Read Abstract +

Pedestrian trajectory prediction is a key prerequisite for path planning and decision-making in autonomous driving. Most of the works based on graph neural network only deal with the dimension of spatio-temporal fusion, ignoring the trajectory features of individual pedestrians and the interaction features between pedestrians. In addition, the uncertainty of pedestrian movement and the potential inherent bias caused by the dynamic changes of surrounding environment and other factors are also rarely considered. We propose an bias correction strategy incorporating spatiotemporal attention networks to mitigate the negative impact of inherent bias on predictions in real environments. First, we extract temporal dependencies and pedestrian interactions in temporal and spatial dimensions, respectively, and construct a bias tensor to model the inherent bias; further, the bias tensor information is decoded, and then the deviation calculation is performed with the decoded original trajectory information, and then the correction of the trajectory prediction is realized. Experimental results on ETH and UCY datasets demonstrate the superiority of our strategy.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years