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In this paper, the idea of client verification in distributed systems is presented. The proposed solution presents a sample system where client verification through cloud resources using input signature is discussed. For different signatures the proposed method has been examined. Research results are presented and discussed to show potential advantages.
This paper tackles the problem of estimating non-rigid human 3D shape and motion from image sequences taken by uncalibrated cameras. Similar to other state-of-the-art solutions we factorize 2D observations in camera parameters, base poses and mixing coefficients. Existing methods require sufficient camera motion during the sequence to achieve a correct 3D reconstruction. To obtain convincing 3D reconstructions...
A solution to long distance outdoor face recognition is presented in this work. The proposed method, called the Two-Stage Alignment/Enhancement Filtering (TAEF) system, consists of three main components: a cross-distance face alignment technique, a cross-environment face enhancement technique, and a two-stage filtering system. Given a probe image, the procedure of face alignment, enhancement and matching...
In this paper I will present a technique to generate a digital signature for an image, which will uniquely identify it, using Radon transform. Even if Radon based approaches are broadly applicable to tomography (the construction of an image from the projection data related with cross-sectional scans of it), in this research work I will show how it can be successfully utilized to classify images and...
We present a novel real time 3D Automatic Target Recognition algorithm appropriate for LIDAR based time critical applications. Its main contribution is the Constant False Alarm Rate adaptive threshold combined with the Projection Density Energy and the transformation of the 3D problem into multiple 2Ds. Our approach is invariant to 3D rotations combined with scale change, Gaussian noise and uniform...
Object tracking is one of the most important topics in computer vision. While the state-of-the-art tracking algorithms achieved great success, there are still some challenging problems to be solved. Firstly, it remains a tough task to develop a tracking algorithm with both accuracy and efficiency. Secondly, the ground truth is often given by a rectangular bounding box, which contains not only the...
By systematically varying the number of subjects and the number of frames per subject, we explored the influence of training set size on appearance and shape-based approaches to facial action unit (AU) detection. Digital video and expert coding of spontaneous facial activity from 80 subjects (over 350,000 frames) were used to train and test support vector machine classifiers. Appearance features were...
This paper proposes a novel local depth and surface normals descriptor to explore the discriminative features on the nasal surface and the adjoining cheek regions for expression robust 3D face recognition. After preprocessing the 3D face data, landmarks located on the perimeter of a triangular region covering the nose and adjoining parts of the cheeks are accurately detected. Inspired by Local Binary...
Gabor features have been used widely in face identification because of their good results and robustness. However, face identification is strongly affected when the test images are very different from those of the gallery, as is the case in varying face pose. In this paper, a new 2D Gabor-based method is proposed that modifies the grid from which the Gabor features are extracted using a mesh to model...
New elevation models from the Czech Republic are produced using airborne laser scanning. These new elevation models achieve much higher accuracy than previous models whose accuracy is expressed in meters. Declared accuracy was subjected to verification in five selected locations. Despite some problems with accuracy, especially in areas of significant microrelief shapes, these models comply the declared...
In this paper, we explore a new algorithm to detect people with thermal cameras based on the standard Implicit Shape Model (ISM) technique. Our approach starts with the ISM to define the proposed centers of people locations. Then we utilize a novel method to detect people based on the density of the concentrated proposed centers by using an auto generated threshold mechanism. Our method is easy to...
Recently, many approaches have been proposed for complete 3D reconstruction of moving objects. Particularly, one-shot reconstruction using a projector-camera system (pro-cam) has attracted considerable attention as it can reconstruct the full 3D shape from a single image and it is therefore suitable for capturing moving objects. However, one-shot measurement methods have the issue that the projection...
This paper presents a method to transfer functional grasps among objects of the same category through contact warping and local replanning. The method transfers implicit knowledge that enables an action on a class of objects for which no explicit grasp or task information has been given in advance. Contact points on the source object are warped based on global and local shape similarities to the target...
Finger vein is a new and promising trait in biometric recognition and some related progress have been achieved in recent years. Considering that there are many different sensors in a biometric system, sensor interoperability is a very important issue and still neglected in the state-of-the-art finger vein recognition. Based on the analysis of the shortcomings in the current finger vein ROI extraction...
Nose tip localization is an important step for registration, preprocessing and recognition of 3D face data. In this paper, we propose a new approach for the nose tip detection that is robust to pose and expression variations and in presence of occlusions. From a rotated 3D face, we extract facial curves that are matched to a profile curve model. An optimal matching using the Riemannian geometry, based...
In this paper, Krawtchouk invariant moments are used as features for object recognition. For hand images, the performance of Krawtchouk moments in terms of recognition accuracy, rotational invariance, scale invariance, computational time and feature vector size, has been analysed. A user independent dataset for 21 subjects under varying illumination conditions is created. A comparative analysis with...
In this paper, we introduce a dictionary learning framework using RGB-D covariance descriptors on point cloud data for performing object classification. Dictionary learning in combination with RGB-D covariance descriptors provides a compact and flexible description of point cloud data. Furthermore, the proposed framework is ideal for updating and sharing dictionaries among robots in a decentralized...
Automatic face recognition across large pose changes is still a challenging problem. Previous solutions apply a transform in image space or feature space for normalizing the pose mismatch. For feature transform, the feature vector extracted on a probe facial image is transferred to match the gallery condition with regression models. Usually, the regression models are learned from paired gallery-probe...
As much information as possible should be used when identifying subjects in surveillance video due to the poor quality and resolution. So far, little attention has been paid to exploiting clothing as it has been considered unlikely to be a potential cue to identity. Clothing analysis could not only potentially improve recognition, but could also aid in subject re-identification. Further, we show here...
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