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In this paper, we present the computational tools and a hardware prototype for 3D face recognition. Full automation is provided through the use of advanced multistage alignment algorithms, resilience to facial expressions by employing a deformable model framework, and invariance to 3D capture devices through suitable preprocessing steps. In addition,(More)
From a user’s perspective, face recognition is one of the most desirable biometrics, due to its non-intrusive nature; however, variables such as face expression tend to severely affect recognition rates. We have applied to this problem our previous work on elastically adaptive deformable models to obtain parametric representations of the geometry of(More)
A 3D landmark detection method for 3D facial scans is presented and thoroughly evaluated. The main contribution of the presented method is the automatic and pose-invariant detection of landmarks on 3D facial scans under large yaw variations (that often result in missing facial data), and its robustness against large facial expressions. Three-dimensional(More)
As the size of the available collections of 3D objects grows, database transactions become essential for their management with the key operation being retrieval (query). Large collections are also precategorized into classes so that a single class contains objects of the same type (e.g., human faces, cars, four-legged animals). It is shown that general(More)
A novel method for the reconstruction of 3D shape and texture from Integral Photography (IP) images is presented. Sharing the same principles with stereoscopic-based object reconstruction, it offers increased robustness to noise and occlusions due to the unique characteristics of IP images. A coarse to fine approach is used, employing a novel grid(More)
The uncontrolled conditions of real-world biometric applications pose a great challenge to any face recognition approach. The unconstrained acquisition of data from uncooperative subjects may result in facial scans with significant pose variations along the yaw axis. Such pose variations can cause extensive occlusions, resulting in missing data. In this(More)
Eurographics W orkshop on 3D Object Retrie v al (2008) I. Pratikakis and T. Theoharis (Editors) Abstract We present a novel 3D object retrieval method that relies upon a hybrid descriptor which is composed of 2D features based on depth buffers and 3D features based on spherical harmonics. To compensate for rotation, two alignment methods, namely CPCA and(More)
It is becoming increasingly important to be able to credential and identify authorized personnel at key points of entry. Such identity management systems commonly employ biometric identifiers. In this paper, we present a novel multimodal facial recognition approach that employs data from both visible spectrum and thermal infrared sensors. Data from multiple(More)
The availability of 3D facial datasets is rapidly growing, mainly as a result of medical and biometric applications. These applications often require the retrieval of specific facial areas (such as the nasal region). The most crucial step in facial region retrieval is the detection of key 3D facial landmarks (e.g., the nose tip). A key advantage of 3D(More)
We present a novel approach for computing a com­ pact and highly discriminant biometric signature for 3D face recognition using linear dimensionality reduction tech­ niques. Initially, a geometry-image representation is used to effectively resample the raw 3D data. Subsequently, a wavelet transform is applied and a biometric signa­ ture composed of 7,200(More)