Slice position-shifting and multi-scale inter-frame proportional fusion network for video-based pedestrian re-identification

Ketao Du; Chen Ma; Askar Hamdulla

doi:10.1117/12.2683292

26 June 2023 Slice position-shifting and multi-scale inter-frame proportional fusion network for video-based pedestrian re-identification

Ketao Du, Chen Ma, Askar Hamdulla

Author Affiliations +

Proceedings Volume 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023); 1272112 (2023) https://doi.org/10.1117/12.2683292
Event: 2023 2nd International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2023, Chengdu, China

Abstract

Different from image-based pedestrian re-identification, video-based pedestrian re-identification has more available information because of more temporal information. However, previous methods are unable to extract detailed features adequately. Although the previous methods adopted the row slicing method to extract the detailed features of the image, the slicing method was too simple and the detailed features extracted were too few. We propose a slice position shifting module (SPM), which adopts a variety of ways to slice the image, to extract the feature of each image patches separately. The feature interaction is carried out by making each patches of the image generate position-shifting. How to make time clues in pedestrian re-identification data set useful is also the research focus in this field. We propose a multi-scale inter-frame proportional fusion module (MIPM) to make the features of frame fully fuse with the front and back frames, so as to extract more the temporal clues in the data set. We will form the above two modules into slice position-shifting and multi-scale inter-frame proportional fusion network (SMnet). Full experiments on the MARS dataset show that our algorithm is very useful and can reach the leading level.

Citation Download Citation

Ketao Du, Chen Ma, and Askar Hamdulla "Slice position-shifting and multi-scale inter-frame proportional fusion network for video-based pedestrian re-identification", Proc. SPIE 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 1272112 (26 June 2023); https://doi.org/10.1117/12.2683292

ACCESS THE FULL ARTICLE

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: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Finite element methods

Feature extraction

Convolution

Video

Image fusion

Mars

Feature fusion

Show All Keywords

Keywords/Phrases

Search In:

Publication Years