Boosting Speed and Accuracy in Deformable Part Models for Face Image in the Wild

2015 ◽  
Author(s):  
Dinh-Luan Nguyen ◽  
Vinh-Tiep Nguyen ◽  
Minh-Triet Tran ◽  
Atsuo Yoshitaka
Keyword(s):  
Face Image ◽  
In The Wild ◽  
Deformable Part Models ◽  
Speed And Accuracy

Manipulating Face Gender

1998 ◽  
Vol 06 (03) ◽  
pp. 219-239 ◽  
Author(s):  
Kenneth A. Deffenbacher ◽  
Cheryl Hendrickson ◽  
Alice J. O'Toole ◽  
David P. Huff ◽  
Hervé Abdi
Keyword(s):  
Face Recognition ◽  
Computational Model ◽  
Face Image ◽  
Gender Classification ◽  
Statistical Features ◽  
Female Adult ◽  
Recognition Experiment ◽  
Accuracy Data ◽  
Speed And Accuracy ◽  
Weighted Combination

Previous research has shown that faces coded as pixel-based images may be constructed from an appropriately weighted combination of statistical "features" (eigenvectors) which are useful for discriminating members of a learned set of images. We have shown previously that two of the most heavily weighted features are important in predicting face gender. Using a simple computational model, we adjusted weightings of these features in more masculine and more feminine directions for both male and female adult Caucasian faces. In Experiment 1, cross-gender face image alterations (e.g., feminizing male faces) reduced both gender classification speed and accuracy for young adult Caucasian observers, whereas same-gender alterations (e.g., masculinizing male faces) had no effect as compared to unaltered controls. Effects on femininity-masculinity ratings mirrored those obtained on gender classification speed and accuracy. We controlled statistically for possible effects of image distortion incurred by our gender manipulations. In Experiment 2 we replicated the same pattern of accuracy data. Combined, these data indicate the psychological relevance of the features derived from the computational model. Despite having different effects on the ease of gender classification, neither sort of gender alteration negatively impacted face recognition (Experiment 3), yielding evidence for a model of face recognition wherein gender and familiarity processing proceed in parallel.

scholarly journals Analysis of Face Recognition Algorithm: Dlib and OpenCV

2020 ◽  
Vol 4 (1) ◽  
pp. 173-184
Author(s):  
Suwarno Suwarno ◽  
Kevin Kevin
Keyword(s):  
Face Recognition ◽  
Facial Recognition ◽  
Real Life ◽  
Recognition Algorithm ◽  
Speed Test ◽  
Recognition Algorithms ◽  
Image Dataset ◽  
In The Wild ◽  
Speed Accuracy ◽  
Speed And Accuracy

In face recognition there are two commonly used open-source libraries namely Dlib and OpenCV. Analysis of facial recognition algorithms is needed as reference for software developers who want to implement facial recognition features into an application program. From Dlib algorithm to be analyzed is CNN and HoG, from OpenCV algorithm is DNN and HAAR Cascades. These four algorithms are analyzed in terms of speed and accuracy. The same image dataset will be used to test, along with some actual images to get a more general analysis of how algorithm will appear in real life scenarios. The programming language used for face recognition algorithms is Python. The image dataset will come from LFW (Labeled Faces in the Wild), and AT&T, both of which are available and ready to be downloaded from the internet. Pictures of people around the UIB (Batam International University) is used for actual images dataset. HoG algorithm is fastest in speed test (0.011 seconds / image), but the accuracy rate is lower (FRR = 27.27%, FAR = 0%). DNN algorithm is the highest in level of accuracy (FRR = 11.69%, FAR = 2.6%) but the lowest speed (0.119 seconds / picture). There is no best algorithm, each algorithm has advantages and disadvantages.Keywords: Python, Face Recognition, Analysis, Speed, Accuracy.

The Research of Face Recognition Method Based on Wavelet Transform

2012 ◽  
Vol 442 ◽  
pp. 463-467
Author(s):  
Li Hong Bi ◽  
Yan Fang Ma ◽  
Li Hua Piao
Keyword(s):  
Face Recognition ◽  
Wavelet Transform ◽  
Principal Component ◽  
Face Image ◽  
Biometric Identification ◽  
Recognition Method ◽  
Image Block ◽  
The Face ◽  
Speed And Accuracy ◽  
Great Development

Face recognition is a kind of biometric identification technology possessing great development potential, researching on this technology has great theoretical values. The paper presents a method of image block principal component analysis (PCA) based on wavelet transform. The image was firstly disposed by wavelet transform and segmented, then we set the different weight values for each of parts according to the different role in the overall image and extract eigenvector using the PCA, finally, the face image is recognized according to the eigenvector and feature. This method can improve the speed and accuracy, reduce the complexity of feature extraction and improve the speed of recognition.

scholarly journals FRGAN: A Blind Face Restoration with Generative Adversarial Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Tongxin Wei ◽  
Qingbao Li ◽  
Zhifeng Chen ◽  
Jinjin Liu
Keyword(s):  
Activation Function ◽  
Human Motion ◽  
Face Image ◽  
Head Pose Estimation ◽  
Generative Adversarial Networks ◽  
3D Face Reconstruction ◽  
Adversarial Networks ◽  
The Face ◽  
In The Wild ◽  
Facial Images

Recent works based on deep learning and facial priors have performed well in superresolving severely degraded facial images. However, due to the limitation of illumination, pixels of the monitoring probe itself, focusing area, and human motion, the face image is usually blurred or even deformed. To address this problem, we properly propose Face Restoration Generative Adversarial Networks to improve the resolution and restore the details of the blurred face. They include the Head Pose Estimation Network, Postural Transformer Network, and Face Generative Adversarial Networks. In this paper, we employ the following: (i) Swish-B activation function that is used in Face Generative Adversarial Networks to accelerate the convergence speed of the cross-entropy cost function, (ii) a special prejudgment monitor that is added to improve the accuracy of the discriminant, and (iii) the modified Postural Transformer Network that is used with 3D face reconstruction network to correct faces at different expression pose angles. Our method improves the resolution of face image and performs well in image restoration. We demonstrate how our method can produce high-quality faces, and it is superior to the most advanced methods on the reconstruction task of blind faces for in-the-wild images; especially, our 8 × SR SSIM and PSNR are, respectively, 0.078 and 1.16 higher than FSRNet in AFLW.

Freeze-substituted fungal cells of Nectria haematococca: A comparison of the macroconidial walls of the adhesion-competent wild type with an adhesion-reduced mutant

1990 ◽  
Vol 48 (3) ◽  
pp. 688-689
Author(s):  
Thecan Caesar-Ton That ◽  
Lynn Epstein
Keyword(s):  
Freeze Substitution ◽  
Uranyl Acetate ◽  
Wild Type ◽  
Nectria Haematococca ◽  
Fruit Extract ◽  
Dialysis Tubing ◽  
Tube Emergence ◽  
Contrast Microscopy ◽  
In The Wild ◽  
Freeze Damage

Nectria haematococca mating population I (anamorph, Fusarium solani) macroconidia attach to its host (squash) and non-host surfaces prior to germ tube emergence. The macroconidia become adhesive after a brief period of protein synthesis. Recently, Hickman et al. (1989) isolated N. haematococca adhesion-reduced mutants. Using freeze substitution, we compared the development of the macroconidial wall in the wild type in comparison to one of the mutants, LEI.Macroconidia were harvested at 1C, washed by centrifugation, resuspended in a dilute zucchini fruit extract and incubated from 0 - 5 h. During the incubation period, wild type macroconidia attached to uncoated dialysis tubing. Mutant macroconidia did not attach and were collected on poly-L-lysine coated dialysis tubing just prior to freezing. Conidia on the tubing were frozen in liquid propane at 191 - 193C, substituted in acetone with 2% OsO4 and 0.05% uranyl acetate, washed with acetone, and flat-embedded in Epon-Araldite. Using phase contrast microscopy at 1000X, cells without freeze damage were selected, remounted, sectioned and post-stained sequentially with 1% Ba(MnO4)2 2% uranyl acetate and Reynold’s lead citrate. At least 30 cells/treatment were examined.

Comparison of Auditory, Language, Memory, and Attention Abilities in Children With and Without Listening Difficulties

2020 ◽  
Vol 29 (4) ◽  
pp. 710-727
Author(s):  
Beula M. Magimairaj ◽  
Naveen K. Nagaraj ◽  
Alexander V. Sergeev ◽  
Natalie J. Benafield
Keyword(s):  
Auditory Processing ◽  
Short Term Memory ◽  
Group Differences ◽  
Long Term Memory ◽  
Short Term ◽  
Significant Group ◽  
Term Memory ◽  
Memory And Attention ◽  
Speed And Accuracy

Objectives School-age children with and without parent-reported listening difficulties (LiD) were compared on auditory processing, language, memory, and attention abilities. The objective was to extend what is known so far in the literature about children with LiD by using multiple measures and selective novel measures across the above areas. Design Twenty-six children who were reported by their parents as having LiD and 26 age-matched typically developing children completed clinical tests of auditory processing and multiple measures of language, attention, and memory. All children had normal-range pure-tone hearing thresholds bilaterally. Group differences were examined. Results In addition to significantly poorer speech-perception-in-noise scores, children with LiD had reduced speed and accuracy of word retrieval from long-term memory, poorer short-term memory, sentence recall, and inferencing ability. Statistically significant group differences were of moderate effect size; however, standard test scores of children with LiD were not clinically poor. No statistically significant group differences were observed in attention, working memory capacity, vocabulary, and nonverbal IQ. Conclusions Mild signal-to-noise ratio loss, as reflected by the group mean of children with LiD, supported the children's functional listening problems. In addition, children's relative weakness in select areas of language performance, short-term memory, and long-term memory lexical retrieval speed and accuracy added to previous research on evidence-based areas that need to be evaluated in children with LiD who almost always have heterogenous profiles. Importantly, the functional difficulties faced by children with LiD in relation to their test results indicated, to some extent, that commonly used assessments may not be adequately capturing the children's listening challenges. Supplemental Material https://doi.org/10.23641/asha.12808607

Dual Goals for Speed and Accuracy on the Same Performance Task

2012 ◽  
Vol 11 (3) ◽  
pp. 118-126 ◽  
Author(s):  
Olive Emil Wetter ◽  
Jürgen Wegge ◽  
Klaus Jonas ◽  
Klaus-Helmut Schmidt
Keyword(s):  
Memory Scanning ◽  
Performance Task ◽  
Performance Tasks ◽  
Trade Off ◽  
Test Experiment ◽  
Trade Offs ◽  
New Finding ◽  
Sternberg Paradigm ◽  
Speed Accuracy ◽  
Speed And Accuracy

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.

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