Paper Info
Title
A rotation and scale invariant technique for ear detection in 3D
Abstract
This paper presents a technique for automatic ear detection from 3D profile face range images. The proposed technique localizes ear by using inherent structural details of the ear in 3D range data and is invariant to rotation and scale. It makes use of connected components of a graph constructed using the edges of the depth map image of the range data. The main advantages of the proposed technique over other existing techniques are of two folds. First, the proposed technique does not require any registered 2D image for the detection of ear in 3D. Second, it is inherently rotation and scale invariant and can detect left and right ear simultaneously without imposing any additional computational cost. To demonstrate the effectiveness of the technique, experiments are conducted on University of Notre Dame public database, Collection J2 (UND-J2) which consists of 3D profile face range images with scale and pose variations. Experimental results are found to be encouraging and reveal the effectiveness of the proposed technique. Results are also compared with the existing 3D ear detection techniques.
Year
DOI
Venue
2012
10.1016/j.patrec.2012.02.021
Pattern Recognition Letters
Keywords
Field
DocType
depth map image,right ear,profile face range image,existing technique,proposed technique,ear detection technique,automatic ear detection,scale invariant technique,scale invariant,range data,proposed technique localizes ear,biometrics
Ear recognition,Graph,Computer vision,Scale invariance,Pattern recognition,Artificial intelligence,Connected component,Invariant (mathematics),Biometrics,Depth map,Mathematics
Journal
Volume
Issue
ISSN
33
14
0167-8655
Citations 
PageRank 
References 
3
0.39
20
Authors
2
Name
Order
Citations
PageRank
Surya Prakash115919.79
Phalguni Gupta280582.58