Mr. Peng Yang Profile

Peng Yang

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 | 19 July 2024 Paper

Improved FCOS algorithm for vehicle pedestrian object detection

Dong Wang, Lei Mi, Peng Yang

Proceedings Volume 13181, 131812K (2024) https://doi.org/10.1117/12.3031270

KEYWORDS: Object detection, Target detection, Detection and tracking algorithms

Read Abstract +

To address issues such as low accuracy in vehicle and pedestrian detection and slow inference speed, an improved version of the FCOS object detection algorithm is proposed. The algorithm replaces the original backbone with ResNet18 and incorporates deformable convolution to enhance its ability to capture shape features of the targets, thereby improving feature extraction and model inference speed. A coarse localization box mechanism is added to the algorithm's localization detection head branch to improve the model's classification accuracy and detection box recall. A new background prediction branch is introduced to enhance the model's detection capability for positive samples by predicting the probability of differences with the environment. Additionally, an ATSS (Adaptive Training Sample Selection) label assignment scheme and GFocal Loss function are employed to replace the original label assignment scheme and loss function, mitigating the impact of imbalances between positive and negative samples in the dataset. The experimental results show that the improved algorithm achieves 94.7% on the KITTI traffic target data set, which is 22.2% higher than the original FCOS model, improves the inference speed to 74 pieces per second, and has better effect compared with some mainstream target detection algorithms.

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