Proceedings ArticleDOI
On the Use of SIFT Features for Face Authentication
Manuele Bicego,Andrea Lagorio,Enrico Grosso,Massimo Tistarelli +3 more
- pp 35-35
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TLDR
This paper investigates the application of the SIFT approach in the context of face authentication, and proposes and tests different matching schemes using the BANCA database and protocol, showing promising results.Abstract:Â
Several pattern recognition and classification techniques have been applied to the biometrics domain. Among them, an interesting technique is the Scale Invariant Feature Transform (SIFT), originally devised for object recognition. Even if SIFT features have emerged as a very powerful image descriptors, their employment in face analysis context has never been systematically investigated. This paper investigates the application of the SIFT approach in the context of face authentication. In order to determine the real potential and applicability of the method, different matching schemes are proposed and tested using the BANCA database and protocol, showing promising results.read more
Citations
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Journal ArticleDOI
Local Binary Patterns and Its Application to Facial Image Analysis: A Survey
TL;DR: As a typical application of the LBP approach, LBP-based facial image analysis is extensively reviewed, while its successful extensions, which deal with various tasks of facial imageAnalysis, are also highlighted.
Journal ArticleDOI
Scale Invariant Feature Transform
TL;DR: The SIFT descriptor has been proven to be very useful in practice for robust image matching and object recognition under real-world conditions and has also been extended from grey-level to colour images and from 2-D spatial images to 2+1-D spatio-temporal video.
Journal ArticleDOI
Partial Face Recognition: Alignment-Free Approach
TL;DR: It is argued that a probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors by adopting a variable-size description which represents each face with a set of keypoint descriptors.
Proceedings ArticleDOI
Oriented Response Networks
TL;DR: Active rotating filters (ARFs) as mentioned in this paper can be used to produce within-class rotation-invariant deep features while maintaining inter-class discrimination for classification tasks, which can also be used for image and object orientation estimation.
Proceedings ArticleDOI
Face recognition using sift features
Cong Geng,Xudong Jiang +1 more
TL;DR: Two new approaches are proposed: Volume-SIFT (VSIFT) and Partial-Descriptor-Sift (PDSIFT) for face recognition based on the original SIFT algorithm, which can achieve comparable performance as the most successful holistic approach ERE and significantly outperforms FLDA and NLDA.
References
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Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Proceedings ArticleDOI
Object recognition from local scale-invariant features
TL;DR: Experimental results show that robust object recognition can be achieved in cluttered partially occluded images with a computation time of under 2 seconds.
Journal ArticleDOI
Face recognition: A literature survey
TL;DR: In this paper, the authors provide an up-to-date critical survey of still-and video-based face recognition research, and provide some insights into the studies of machine recognition of faces.
Proceedings ArticleDOI
PCA-SIFT: a more distinctive representation for local image descriptors
Yan Ke,Rahul Sukthankar +1 more
TL;DR: This paper examines (and improves upon) the local image descriptor used by SIFT, and demonstrates that the PCA-based local descriptors are more distinctive, more robust to image deformations, and more compact than the standard SIFT representation.
Journal ArticleDOI
Face recognition by elastic bunch graph matching
TL;DR: A system for recognizing human faces from single images out of a large database containing one image per person, based on a Gabor wavelet transform, which is constructed from a small get of sample image graphs.