Person Re-identification in Wide Area Camera Networks

Shah, Shishir K.; Bedagkar-Gala, Apurva

doi:10.1007/8612_2012_7

Cited by 1 publication

(1 citation statement)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In conventional methodologies, numerous endeavors have been made to extract three-dimensional data from videos for appearance representation, as exemplified by HOG3D [29]and 3DSIFT [30], which stem from widely employed 2-D extensions. Many researchers explore video-based pedestrian re-identification challenges using gait analysis [31]. However, acquiring gait information necessitates details about pedestrian outlines or body parts, disregarding pedestrians' appearance information.…”

Section: Based On Video-based Person Re-identificationmentioning

confidence: 99%

Deep learning in person re-identification: a survey

Xiao,

Zhang,

Ning

et al. 2024

International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024)

View full text Add to dashboard Cite

In the era of advancing deep learning, person re-identification has gained widespread application in domains such as video and security monitoring. Person re-identification seeks to recognize and match target persons across images taken by diverse cameras, thereby verifying whether the pedestrian subjects observed by cameras at various locations and times are indeed the same individual. This article categorizes current research into two main types: image-based person reidentification and video-based person re-identification. It provides a thorough overview and analysis of existing literature concerning classification methods, verification models, attention mechanisms, and metric learning,all centered around the research subjects. Additionally, it outlines the progression of datasets and provides insights into the anticipated future trends in person re-identification

show abstract

Section: Based On Video-based Person Re-identificationmentioning

confidence: 99%