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We propose a facial landmarks detector, in which a part-based model is incorporated with holistic face information. In the part-based model, the face is modeled by the appearance of different face parts and their geometric relation. The appearance is described by pixel normalized difference descriptor. This descriptor is the lowest computational complexity as compared with existing state-of-the-art...
Human activity recognition (HAR) is the basis for many real world applications concerning health care, sports and gaming industry. Different methodological perspectives have been proposed to perform HAR. One appealing methodology is to take an advantage of data that are collected from inertial sensors which are embedded in the individual's smartphone. These data contain rich amount of information...
In this study, the experimental studies were carried out on a database containing the types of wood knot. After preprocessing on the images in the database, specific features to knot were obtained using wavelet moments feature extraction algorithm. Type description is carried out with KNN classification algorithm by selecting most distinguishing the approximation coefficients on these features. In...
This paper examines the effectiveness of geometric feature descriptors, common in computer vision, for false positive reduction and for classification of lung nodules in low dose CT (LDCT) scans. A data-driven lung nodule modeling approach creates templates for common nodule types, using active appearance models (AAM); which are then used to detect candidate nodules based on optimum similarity measured...
We present a novel method to detect when a person is speaking using respiratory measurements collected in the natural environment. A speaker's respiration pattern is sampled from a respiratory inductive plethysmograph (RIP) band worn around the speaker's chest. Ratio of inhalation duration to exhalation duration (IE ratio) has traditionally been used to detect speaking in controlled lab environment...
Repeated exposures to psychological stress can lead to or worsen diseases of slow accumulation such as heart diseases and cancer. The main challenge in addressing the growing epidemic of stress is a lack of robust methods to measure a person's exposure to stress in the natural environment. Periodic self-reports collect only subjective aspects, often miss stress episodes, and impose significant burden...
Biometrics has become more and more important in security applications. In comparison with many other biometrie features, iris recognition has very high recognition accuracy. Successful iris recognition matching depends on how similar the stored template in database is compared with the introduced template. The main objective of this paper is to introduce a high performance scheme for iris recognition...
Breast cancer is the most common cancer in many countries all over the world. Early detection of cancer, in either diagnosis or screening programs, decreases the mortality rates. Computer Aided Detection (CAD) is software that aids radiologists in detecting abnormalities in medical images. In this article we present our approach in detecting abnormalities in mammograms using digital mammography. Each...
We propose a framework for face recognition at a distance based on texture and sparse-stereo reconstruction. We develop a 3D acquisition system that consists of two CCD stereo cameras mounted on pan-tilt units with adjustable baseline. We first detect the facial region and extract its landmark points, which are used to initialize the face alignment algorithm. The fitted mesh vertices, generated from...
This paper introduces a framework for long-distance face recognition using dense and sparse stereo reconstruction, with texture of the facial region. Two methods to determine correspondences of the stereo pair are used in this paper: (a) dense global stereo-matching using maximum-a-posteriori Markov Random Fields (MAP-MRF) algorithms and (b) Active Appearance Model (AAM) fitting of both images of...
In a human-robot interface, the prediction of motion, which is based on context information of a task, has the potential to improve the robustness and reliability of motion classification to control human-assisting manipulators. The electromyography (EMG) signals can be used as a control source of artificial arm after it has been processed. The objective of this work is to achieve better classification...
We describe a framework for face recognition at a distance based on sparse-stereo reconstruction. We develop a 3D acquisition system that consists of two CCD stereo cameras mounted on pan-tilt units with adjustable baseline. We first detect the facial region and extract its landmark points, which are used to initialize an AAM mesh fitting algorithm. The fitted mesh vertices provide point correspondences...
This paper presents a lossless data hiding approach based on integer wavelet transform and variable threshold for a novel application of watermarking. In this novel application, a depth map of an object obtained from sequence of 2D images is secretly embedded in one of the 2-D images for subsequent 3-D analysis after transmission. Additionally, for efficient generation of the depth map, we also propose...
The typical optical character recognition (OCR) systems, regardless the characterpsilas nature, are based mainly on three stages, preprocessing, features extraction and discrimination (recognizer). Each stage has its own problems and effects on the system efficiency such as time consuming and recognition errors. In order to avoid these difficulties this research paper presents new construction of...
Recently more researchers in the biomedical engineering have introduced many techniques which try to detect epileptic seizures in Electroencephalogram (EEG). The main objective of this paper is to develop technique that is capable of differentiating between epileptic and normal signals. This technique consists of two stages. The first stage is the features extraction and the second stage is the classification...
The paper presents a hybrid technique for affine invariant feature extraction with the view of object recognition. The proposed technique first normalizes an input image by removing affine distortions from it and then spatially re-samples the affine normalized image across multiple scales, next the Gabor transform is computed for the resampled images over different frequencies and orientations. Finally...
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