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Proceedings ArticleDOI

A nonlinear approach for face sketch synthesis and recognition

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TLDR
This paper presents a face recognition system based on face sketches that is based on pseudo-sketch synthesis and sketch recognition, and experimental results show that the performance of the proposed method is encouraging.
Abstract
Most face recognition systems focus on photo-based face recognition. In this paper, we present a face recognition system based on face sketches. The proposed system contains two elements: pseudo-sketch synthesis and sketch recognition. The pseudo-sketch generation method is based on local linear preserving of geometry between photo and sketch images, which is inspired by the idea of locally linear embedding. The nonlinear discriminate analysis is used to recognize the probe sketch from the synthesized pseudo-sketches. Experimental results on over 600 photo-sketch pairs show that the performance of the proposed method is encouraging.

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Citations
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Journal ArticleDOI

Face Photo-Sketch Synthesis and Recognition

TL;DR: A novel face photo-sketch synthesis and recognition method using a multiscale Markov Random Fields (MRF) model that allows effective matching between the two in face sketch recognition.
Journal ArticleDOI

Multi-View Discriminant Analysis

TL;DR: This work proposes a Multi-view Discriminant Analysis (MvDA) approach, which seeks for a single discriminant common space for multiple views in a non-pairwise manner by jointly learning multiple view-specific linear transforms.
Proceedings ArticleDOI

Bypassing synthesis: PLS for face recognition with pose, low-resolution and sketch

TL;DR: This paper uses Partial Least Squares to linearly map images in different modalities to a common linear subspace in which they are highly correlated, and forms a generic intermediate subspace comparison framework for multi-modal recognition.
Journal ArticleDOI

A Comprehensive Survey to Face Hallucination

TL;DR: This paper comprehensively surveys the development of face hallucination, including both face super-resolution and face sketch-photo synthesis techniques, and presents a comparative analysis of representative methods and promising future directions.
Journal ArticleDOI

Heterogeneous Face Recognition Using Kernel Prototype Similarities

TL;DR: A generic HFR framework is proposed in which both probe and gallery images are represented in terms of nonlinear similarities to a collection of prototype face images, and Random sampling is introduced into the H FR framework to better handle challenges arising from the small sample size problem.
References
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Journal ArticleDOI

Nonlinear dimensionality reduction by locally linear embedding.

TL;DR: Locally linear embedding (LLE) is introduced, an unsupervised learning algorithm that computes low-dimensional, neighborhood-preserving embeddings of high-dimensional inputs that learns the global structure of nonlinear manifolds.
Journal ArticleDOI

Eigenfaces for recognition

TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
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.
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.
Proceedings ArticleDOI

Fisher discriminant analysis with kernels

TL;DR: In this article, a non-linear classification technique based on Fisher's discriminant is proposed and the main ingredient is the kernel trick which allows the efficient computation of Fisher discriminant in feature space.
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