Paper Info
Title
Set-Based Classification For Person Re-Identification Utilizing Mutual-Information
Abstract
Identifying individuals in multi-view camera network, known as person re-identification, becomes an emerging topic for video surveillance. In this paper, we address person re-identification as a set-based classification problem and introduce mutual-information to fully utilize gallery information. Firstly, we define a set-based structure that contains pairwise features between query image and gallery images. Then these features are fed into a set-class model, which exploits the relationship between set and class label (person identity) using mutual-information. Finally, we estimate and rank the mutual-information scores, and the corresponding label of the highest score is assigned to the query image. Our method has gained a superior performance compared with the stateof-the-art in the benchmark datasets i-LIDS and ETHZ.
Year
Venue
Keywords
2013
2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013)
Person re-identification, mutual information, video surveillance
Field
DocType
ISSN
Computer vision,Pairwise comparison,Pattern recognition,Computer science,Image matching,Image retrieval,Camera network,Feature extraction,Exploit,Mutual information,Artificial intelligence,Contextual image classification
Conference
1522-4880
Citations 
PageRank 
References 
0
0.34
11
Authors
4
Name
Order
Citations
PageRank
Hao Liu111310.67
Lei Qin251527.67
Zhongwei Cheng31076.05
Qingming Huang43919267.71