Face recognition is among the most challenging techniques for personal identity verification. Even though it is so natural for humans, there are still many hidden mechanisms which ...
Massimo Tistarelli, Linda Brodo, Andrea Lagorio, M...
In this paper, we present an effective approach for spatiotemporal face recognition from videos using an Extended set of Volume LBP (Local Binary Pattern features) and a boosting s...
Automated processing of facial images has become a serious market for both hard- and software products. For the commercial success of face recognition systems it is most crucial th...
An automatic personal identification system based solely on fingerprints or faces is often not able to meet the system performance requirements. Face recognition is fast but not ex...
Recent research has shown the effectiveness of using sparse coding(Sc) to solve many computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear sim...
In this paper, we introduce a Hybrid Hidden Markov Model (HMM) face recognition system. The proposed system contains a low-complexity 2-D HMM-based face recognition (LC 2D-HMM FR)...
We describe a scheme to combine the results of audio and face identification for multimedia indexing and retrieval. Audio analysis consists of speech and speaker recognition deri...
Mahesh Viswanathan, Homayoon S. M. Beigi, Alain Tr...
An automatic face recognition system based on multiple facial features is described in this paper. Each facial feature is represented by a Gabor-based complex vector and is locali...
—A representation based on the phase of analytic image is proposed to address the issue of illumination variation in face recognition task. The problem of unwrapping in the compu...
Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The origina...