Paper Info
Title
Using Face Quality Ratings to Improve Real-Time Face Recognition
Abstract
A Face Quality Rating (FQR) is a value derived from a face image that indicates the probability that the face image will be successfully recognized by a specific face recognition method. The FQR can be used as a pre-filter in real-time environments where thousands of face images can be captured every second by multiple surveillance cameras. With so many captured face images, face recognition methods need to strategically decide which face images to attempt recognition on, as it is prohibitively difficult to attempt recognition on all of the images. The FQR pre-filter optimizes processor time utilization resulting in more people being recognized (faster and more accurately) before they leave the surveillance cameras' views. We generate FQR values using Multiple Layered Perceptron (MLP) neural networks. We then use these MLPs in a real-time environment to experimentally prove that FQR pre-filtering improves the speed and accuracy of any real-time face recognition method...
Year
DOI
Venue
2009
10.1007/978-3-540-92957-4_2
PSIVT
Keywords
Field
DocType
real-time environment,multiple layered perceptron,face image,face quality ratings,surveillance camera,fqr pre-filtering,real-time face recognition method,multiple surveillance camera,face recognition method,face quality rating,specific face recognition method,improve real-time face recognition,face recognition,real time
Virtual image,Computer vision,Facial recognition system,Three-dimensional face recognition,Pattern recognition,Computer science,Artificial intelligence,Face detection,Artificial neural network,Perceptron
Conference
Volume
ISSN
Citations 
5414
0302-9743
1
PageRank 
References 
Authors
0.36
11
3
Name
Order
Citations
PageRank
Karl Axnick1202.38
Ray Jarvis232.21
Kim C. Ng3919.38