Paper Info
Title
View Invariant Appearance-Based Person Reidentification Using Fast Online Feature Selection and Score Level Fusion
Abstract
Fast and robust person reidentification is an important task in multi-camera surveillance and automated access control. We present an efficient appearance-based algorithm, able to reidentify a person regardless of occlusions, distance to the camera, and changes in view and lighting. The use of fast online feature selection techniques enables us to perform reidentification in hyper-real-time for a multicamera system, by taking only 10 seconds for evaluating 100 minutes of HD-video data. We demonstrate, that our approach surpasses current appearance-based state-of-theart in reidentification quality and computational speed and sets a new reference in non-biometric reidentification.
Year
DOI
Venue
2012
10.1109/AVSS.2012.81
AVSS
Keywords
Field
DocType
non-biometric reidentification,fast online feature selection,important task,current appearance-based state-of-theart,hd-video data,robust person reidentification,efficient appearance-based algorithm,view invariant appearance-based person,reidentification quality,computational speed,automated access control,score level fusion,real time systems,image fusion,ranking,computational modeling,feature extraction,robustness,object tracking
Computer vision,Ranking,Feature selection,Image fusion,Pattern recognition,Computer science,Feature extraction,Robustness (computer science),Video tracking,Invariant (mathematics),Artificial intelligence,Access control
Conference
Citations 
PageRank 
References 
10
0.58
20
Authors
5
Name
Order
Citations
PageRank
Markus Eisenbach1376.76
Alexander Kolarow2352.95
Konrad Schenk3272.12
Klaus Debes4395.28
Horst-Michael Gross576192.05