A Fast and Fully Automatic Ear Recognition Approach Based on 3D Local Surface Features

Sensitivity of global features to pose, illumination and scale variations encouraged researchers to use local features for object representation and recognition. Availability of 3D scanners also made the use of 3D data (which is less affected by such variations compared to its 2D counterpart) very popular in computer vision applications. In this paper, an approach is proposed for human ear recognition based on robust 3D local features. The features are constructed on distinctive locations in the 3D ear data with an approximated surface around them based on the neighborhood information. Correspondences are then established between gallery and probe features and the two data sets are aligned based on these correspondences. A minimal rectangular subset of the whole 3D ear data only containing the corresponding features is then passed to the Iterative Closest Point (ICP) algorithm for final recognition. Experiments were performed on the UND biometric database and the proposed system achiev...

• Type: Conference
• Year: 2008
• Where: ACIVS
• Authors: Syed M. S. Islam, Rowan Davies, Ajmal S. Mian, Mohammed Bennamoun
• Keywords: ACIVS 2008, Computer Vision, Ear Data, Ear Recognition, Local Features