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This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S3FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces. Specifically, we try to solve the common problem that anchorbased detectors deteriorate dramatically as the objects become smaller. We make contributions in the following three aspects:...
This paper reports on a Q VGA vision sensor embedding 160 column-level digital processors executing real-time tunable scene background subtraction for robust event detection. The single-ramp column-parallel ADCs are used to estimate the pixel variations and detecting anomalous behaviors against two reference images stored in on-chip. The sensor generates a 160×120 pixel bitmap associated to potential...
Over a decade of continual expansion in networking and cloud computing has naturally created an increased demand for cybersecurity solutions. Due to the large number of communication devices and content, it is ideal that these cybersecurity solutions are automated. Unfortunately, malicious content and/or activity is often designed to “look” normal and new malicious attacks are repeatedly being developed...
Novel human gesture recognition and classification technique is suggested and experimentally studied. Suggested strategy is based on exploiting the interactions of human gestures with high-frequency electromagnetic field. Extracting of classification features contained in the wireless radio signal modulated by human gestures is proposed by utilizing bispectrum-based processing of the signal envelope...
Recent studies show that eyebrows can be used as a biometric or soft biometric for recognition. In some scenarios such as partially occluded or covered faces, they can be used for recognition. In this paper, we study eyebrow recognition using texture-based features. We apply features which have not been used before for eyebrow recognition such as 3-patch local binary pattern and WLD (Weber local descriptor)...
The performance of a fingerprint recognition system hinges on the errors introduced in each of its modules: image acquisition, preprocessing, feature extraction, and matching. One of the most critical and fundamental steps in fingerprint recognition is robust and accurate minutiae extraction. Hence we conduct a repeatable and controlled evaluation of one open-source and three commercial-off-the-shelf...
Human action recognition has been extensively studied with a lot of real life application. Many methods have been proposed and achieved promising results when the input video captured from the same viewpoints. However, their accuracy decreases significantly under viewpoint changing. The reason is that action appearance is quite different when looking from a different angle. To overcome this problem,...
A speeding up robust identification scheme for JPEG images is proposed in this paper. The aim of the identification is to robustly identify JPEG images that are generated from the same original image, under various compression conditions such as differences in compression ratios and initial quantization matrices. The conventional scheme that we focus on uses visually protected features to achieve...
This paper describes a face recognition-based people tracking and re-identification system for RGB-D camera networks. The system tracks people and learns their faces online to keep track of their identities even if they move out from the camera's field of view once. For robust people re-identification, the system exploits the combination of a deep neural network- based face representation and a Bayesian...
Paper is focused on problem of robust feature detector stability and efficiency in case when intensity distribution is uneven over image. Results of feature detector simulation and equations for estimation rate of false alarms and probability of correct detection are presented in paper.
Image co-segmentation is the problem of extracting the common objects from multiple images. Foreground segmentation is always effected by the diverse objects and complex background. However, the existing methods didn't pay much attention to images' background as object, especially the similar background. To address the similar scene co-segmentation problems, a method which considers the foreground...
As the usage areas of the images increase, the functions of various image editing software are increasing. Easy-to-use software has caused the images to be tampered with easily. Many Copy-Move Forgery Detection (CMFD) algorithms have been developed against these attacks. In literature CMFD methods are divided into block based and keypoint based methods. In this paper, recent works in keypoint based...
Radio frequency fingerprints (RF fingerprints) extraction is a technology that can identify the unique radio transmitter at the physical level by measuring external feature to match with feature library. RF fingerprints is the reflection of differences between hardwares of transmitters, and it contains rich detail characteristics of internal components within transmitter. RF fingerprints has been...
In this paper we propose a novel efficient method of characteristic image point detection based on the fractional order derivative. The concept of this approach called (FSIFT: Fractional-SIFT) is inspired by the Scale-Invariant Feature Transform (SIFT) proposed by Lowe and can be viewed as a certain generalization of this formula. The classical SIFT detector is implemented efficiently by using a difference...
In this paper, we present a novel approach for real-time object identification on a mobile platform. First, our system detects keypoints within a scaled pyramid-based FAST detector and then descriptors of the object of interest are computed using an Analytical Fourier-Mellin transform. The Fourier-Mellin is used in similarity studies due to its invariance property and discrimination power. In this...
This work presents an original real time, robust micro-expression detection algorithm. The algorithm analyses the movement modifications that occur around the most prominent facial regions using two absolute frame differences. Next, a machine learning algorithm is used to predict if a micro-expression occurred at a given frame t. Two classifiers were evaluated: decision tree and random forest classifier...
Identification and apprehension of criminals by matching facial sketches with photographic faces is one of the major law enforcement applications of the modern world. Majority of the crime occur where there will not be any information available regarding the suspect. In such situation, forensic sketch artist who usually deal with the eyewitness of the crime or victim in order to draw the sketch that...
Biometric technologies are the automated procedures for validating and identifying the originality of an individual. The biometric systems for automatic authentication are fingerprint, iris, retina, voice, hand geometry recognition. Nowadays, the retina recognition has received an importance, as the unique characteristics of the retina. In the acquisition method, the retinal images might experience...
Providing stable and robust power signals for electrical consumers and apparatuses is the most important responsibility of all electric power providers. Whenever the electric power signals suffer from disturbances which affect their quality and consequently peril the safety and right operation of electrical appliances, it is the main task of suppliers to detect and solve such obstacles. For defect...
Previous models based on Deep Convolutional Neural Networks (DCNN) for face verification focused on learning face representations. The face features extracted from the models are applied to additional metric learning to improve a verification accuracy. The models extract high-dimensional face features to solve a multi-class classification. This results in a dependency of a model on specific training...
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