The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Indirect ImmunoFluorescence (IIF) is currently the recommended method for the detection of antinuclear autoantibodies(ANA). It is an effective technique to reveal the presence of auto immune diseases; however, it is a subjective method and hence dependent on the experience and expertise of the physician. Moreover, inter-observer variability limits the reproducibility of IIF reading. To this end, we...
Eye detector and eye tracker have been individually used to solve the task of eye localization in video. Although the eye detection based approach seems to be robust especially in frontal view faces and opened eyes, its performance drops dramatically in the presence of large head pose change and closed eyes. Meanwhile, eye tracking based approaches can estimate closed eyes and eyes in extreme head...
While the performance of Robust Principal Component Analysis (RPCA), in terms of the recovered low-rank matrices, is quite satisfactory to many applications, the time efficiency is not, especially for scalable data. We propose to solve this problem using a novel fast incremental RPCA (FRPCA) approach. The low rank matrices of the incrementally-observed data are estimated using a convex optimization...
In this work, we investigate the applicability of the Kinect depth camera as a robot mounted measurement unit. In contrast to traditional head mounted robot sensors, Kinect is small, cheap and delivers robust depth measurements on a variety of scenes. In the course of applying it on a robot arm, we solve a number of problems: we reduce the sensor working distance to a few centimeters, replace the...
In this paper, we focus on a challenging pattern recognition problem of significant industrial impact: classifying vehicles from their rear videos as observed by a camera mounted on top of a highway with vehicles traveling at high speed. To solve this problem, we present a novel feature called structural signatures. From a rear view video, a structural signature recovers the vehicle side profile information...
We propose a novel local feature descriptor, Local Gaussian Directional Pattern (LGDP), for face recognition. LGDP encodes the directional information of the face's textures (i.e., the texture's structure) in a compact way, producing a more discriminating code than other methods. The structure of each micro-pattern is computed by using a derivative-Gaussian compass mask, and encoded by using its prominent...
This paper addresses the problem of shape classification and proposes a method able to exploit peculiarities of both, local and global shape descriptors. In the proposed shape classification framework, the silhouettes of symbols are firstly described through Bags of Shape Contexts. This shape signature is used to solve correspondence problem between points of two shapes. The obtained correspondences...
This paper proposes a novel active learning method for the classification of motor imagery electroencephalogram (EEG) signals. Specifically, we propose an iterative clustering and support vector-based criterion to select samples of high-confidence to construct a robust training set. The common spatial pattern (CSP)-based features are iteratively clustered till the number of support vectors in the...
Progress in LiDAR scanning has led to the availability of large scale LiDAR datasets for urban areas. We use such pre-acquired data to determine the poses of 2D monocular cameras highly accurately in real-time. This is achieved by first correctly aligning key-frames of the multi-modal data using a combination of feature and intensity-based 2D/3D registration methods. The online pose is then determined...
A novel extension for color images of the local phase quantization (LPQ) local descriptor is presented. The descriptor is obtained by using a multivector representation of color values in order to derive blur-robust features in frequency domain. We tested the proposed descriptor in texture classification problems, and quantified its robustness for several amounts of blur. The experiments show that...
In this paper, we propose a new method to track players using 3D particle filter guided by the time-situation graph in order to perform players tracking robust to occlusion in a soccer image sequence. In the conventional method using particle filter, there is a deficit that it is difficult to discover the players again once they are lost in an image sequence. Thus, we represents the position information...
This paper proposes a prioritized matching approach for finding corresponding points in multiple calibrated images for multi-view stereo reconstruction. The approach takes a sparse set of seed matches between pairs of views as input and then propagates the seeds to neighboring regions by using a prioritized matching method which expands the most promising seeds first. The output of the method is a...
Indirect immunofluorescence (IIF) imaging is a method used for detection of antinuclear auto-antibodies (ANA) for the diagnosis of autoimmune diseases. We present a feature extraction and classification scheme to classify the fluorescence staining patterns of HEp-2 cells in IIF images. We propose a set of complementary features that are sensitive to staining pattern variations among classes. Our feature...
We address the problem of staircase detection, in the context of a navigation aid for the visually impaired. The requirements for such a system are robustness to viewpoint, distance, scale, real-time operation, high detection rate and low false alarm rate. Our approach uses classifiers trained using Haar features and Ad-aboost learning. This first stage does detect staircases, but produces many false...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.