Journal ArticleDOI
Memetically Optimized MCWLD for Matching Sketches With Digital Face Images
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TLDR
An automated algorithm to extract discriminating information from local regions of both sketches and digital face images is presented and yields better identification performance compared to existing face recognition algorithms and two commercial face recognition systems.Abstract:
One of the important cues in solving crimes and apprehending criminals is matching sketches with digital face images. This paper presents an automated algorithm to extract discriminating information from local regions of both sketches and digital face images. Structural information along with minute details present in local facial regions are encoded using multiscale circular Weber's local descriptor. Further, an evolutionary memetic optimization algorithm is proposed to assign optimal weight to every local facial region to boost the identification performance. Since forensic sketches or digital face images can be of poor quality, a preprocessing technique is used to enhance the quality of images and improve the identification performance. Comprehensive experimental evaluation on different sketch databases show that the proposed algorithm yields better identification performance compared to existing face recognition algorithms and two commercial face recognition systems.read more
Citations
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Journal ArticleDOI
Graphical Representation for Heterogeneous Face Recognition
TL;DR: In this article, a graphical representation based HFR method (G-HFR) is proposed to represent heterogeneous image patches separately, which takes the spatial compatibility between neighboring image patches into consideration.
Book ChapterDOI
Heterogeneous Face Recognition with CNNs
Shreyas Saxena,Jakob Verbeek +1 more
TL;DR: Experimental results show that CNNs trained on visible spectrum images can be used to obtain results that are on par or improve over the state-of-the-art for heterogeneous recognition with near-infrared images and sketches.
Journal ArticleDOI
Multiple Representations-Based Face Sketch–Photo Synthesis
TL;DR: A novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch that combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches.
Journal ArticleDOI
A survey on heterogeneous face recognition
TL;DR: This survey provides a comprehensive review of established techniques and recent developments in HFR, and offers a detailed account of datasets and benchmarks commonly used for evaluation.
Journal ArticleDOI
Recognizing disguised faces: human and machine evaluation.
TL;DR: An automated algorithm is developed to verify the faces presented under disguise variations using automatically localized feature descriptors which can identify disguised face patches and account for this information to achieve improved matching accuracy.
References
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Adaptive wavelet thresholding for image denoising and compression
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Journal ArticleDOI
WLD: A Robust Local Image Descriptor
TL;DR: Experimental results on the Brodatz and KTH-TIPS2-a texture databases show that WLD impressively outperforms the other widely used descriptors (e.g., Gabor and SIFT), and experimental results on human face detection also show a promising performance comparable to the best known results onThe MIT+CMU frontal face test set, the AR face data set, and the CMU profile test set.
Journal ArticleDOI
Face Photo-Sketch Synthesis and Recognition
Xiaogang Wang,Xiaoou Tang +1 more
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
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
Natalio Krasnogor,James C. Smith +1 more
TL;DR: This paper reviews some works on the application of MAs to well-known combinatorial optimization problems, and places them in a framework defined by a general syntactic model, which provides them with a classification scheme based on a computable index D, which facilitates algorithmic comparisons and suggests areas for future research.
Journal ArticleDOI
Face Recognition by Humans: Nineteen Results All Computer Vision Researchers Should Know About
TL;DR: Findings from experimental studies of face recognition by humans provide insights into the nature of cues that the human visual system relies upon for achieving its impressive performance and serve as the building blocks for efforts to artificially emulate these abilities.
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