Paper Info
Title
An Efficient 3D Facial Landmark Detection Algorithm with Haar-like Features and Anthropometric Constraints.
Abstract
In the last few years 3D face recognition has become more and more popular due to reducing cost of scanners and increasing computational power. The crucial and time-consuming step is landmark localization and normalization of facial surface. Due to acquisition, noise and other artifacts like spikes and holes occur. Most systems require computational intensive preprocessing steps to eliminate these artifacts. As a consequence, a trade-off between runtime or detection accuracy must be made. In contrast, we propose a landmark detection algorithm which uses the Viola & Jones classifier on gradient images. The algorithm is able to reliably detect landmarks in raw 3D data without complicated preprocessing. Additionally, selection of sub regions is exploited to limit search regions. It further reduces false detection rate and improves significantly detection accuracy.
Year
Venue
Keywords
2013
BIOSIG
face recognition,feature extraction,gradient methods,image classification,object detection,3D face recognition,3D facial landmark detection algorithm,Haar-like features,Viola & Jones classifier,anthropometric constraints,computational intensive preprocessing steps,detection accuracy,gradient images,landmark localization,raw 3D data,time-consuming step
Field
DocType
Citations 
Viola–Jones object detection framework,Computer science,Haar-like features,Artificial intelligence,Facial recognition system,Computer vision,Object detection,Pattern recognition,Three-dimensional face recognition,Object-class detection,Algorithm,Feature extraction,Landmark
Conference
2
PageRank 
References 
Authors
0.38
0
2
Name
Order
Citations
PageRank
Martin Böckeler120.38
Xuebing Zhou215013.14