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.
In this paper, we present a probabilistic approach to segmentation of malignant breast masses which have irregular shape, spiculated margins and which may be embedded in high density glandular tissue. First, we perform contrast enhancement of the image using a simple logarithmic transformation. Then, we derive a segmentation technique based on a specific class of Markov random fields (MRFs) known...
Decisions about cervical cancer diagnosis and classification currently require microscopic examination of cervical tissue by an expert pathologist. In the present study, which focused on full automation of this approach, we solely use nucleus-level features to classify tissues as normal or cancer. We propose Adaptive Nucleus Shape Modeling (ANSM) algorithm for nucleus-level analysis which consists...
In this paper, we propose a novel non-invasive framework for the early diagnosis of prostate cancer from diffusion-weighted magnetic resonance imaging (DW-MRI). The proposed approach consists of three main steps. In the first step, the prostate is localized and segmented based on a new level-set model. In the second step, the apparent diffusion coefficient (ADC) of the segmented prostate volume is...
This paper proposes a blur detection algorithm that is capable of detecting and quantifying the level of spatially-varying blur by integrating directional edge spread calculation, Just Noticeable Blur (JNB) and local probability summation. The proposed method generates a blur map indicating the relative amount of perceived local blurriness. We compare the proposed method with six other state-of-the-art...
In volume seam carving, seam carving for three-dimensional (3D) cost volume, an optimal seam surface can be derived by graph cuts, resulting from sophisticated graph construction. However, the graph cuts algorithm is not suitable for practical use because it incurs a heavy computational load. We propose a multi-pass dynamic programming (DP) based approach for volume seam carving that reduces computation...
Content-aware image retargeting adjusts images to arbitrary sizes and preserves visually salient content. Previous algorithms formulate the problem in terms of either pixel level or mesh level structures, deforming salient objects inconsistently. To improve retargeting quality and reduce complexity, we introduced a patch-wise method to generate sparse image grids based on visual saliency and gradient...
We developed an optical distortion correction technique for an eyeglasses-type wearable device using a multi-mirror array (MMA). This wearable device is small and light weight, but optics using MMA can cause optical distortions, such as geometric distortion and chromatic aberration of magnification, that depend on the user's pupil distance and degrade the visibility of displayed virtual images. We...
We address the problem of full body human pose estimation in video. Most previous work consider body part, pose or trajectory of body part as basic unit to compose the pose sequence. In contrast, we consider tracklet of body part as the basic unit. Based on this medium granularity representation we develop a spatio-temporal graphical model to select an optimal tracklet for each part in each video...
Recently, graph ranking-based methods have been introduced to visual tracking and achieved promising results due to the local structure preserving property. However, existing graph ranking-based trackers use holistic templates to construct the graphs which makes the trackers sensitive to occlusions. In this paper, we propose a part-based multi-graph ranking algorithm for robust visual tracking. In...
Smart living and well aging represent key challenges for our society. The precursor state of adverse outcomes that characterize aging has been recognized from scientific community with the frailty syndrome, determined by the loss of physical and psychological capacities. In this paper we define gait and posture indexes that can be effectively and unobtrusively measured using computer vision and RGBD...
We propose optimal rate-allocation, using viewer attention information among viewpoints, for depth map cameras within a free-viewpoint television broadcast system. An attention-weighted rate-allocation framework enables bit-rate, or quality, to be distributed across the multiple cameras in accordance with viewer interest, minimizing total observed distortions perceived among all viewers. Prior work...
Depth maps are typically made of smooth regions separated by sharp edges. Following this rationale, this paper presents a novel coding scheme where depth data is represented by a set of contours defining the various regions together with a compact representation of the values inside each region. The proposed coding scheme is based on elastic curves, which make possible to compactly represent the contours...
We propose a new compression method devoted to large structured hexahedral meshes having discontinuities. It is dedicated to applications such as visualization or physical simulations whose management by any workstation or mobile device with limited memory and bandwidth is critical. Our method relies on a multiresolution analysis that generates a hierarchy of meshes at increasing resolutions. Our...
As the state-of-the-art video coding standard for 3D video, the 3D video extension of High Efficiency Video Coding (3D-HEVC) compresses the multi-view texture videos plus depth maps. The intra depth coding consumes huge computational complexity due to the added depth modeling modes (DMMs) and its new complex processing flow. This paper proposes a fast algorithm to reduce the complexity for prediction...
We propose a software solution which allows the user to design a realistic illumination for a given 2D image of a face. The user paints a few strokes on the image to give clues of desired novel lighting effects. The algorithm produces an image of the face under the best possible realistic illumination, accordingly. It takes advantage of a 3D Morphable Model framework and a state of the art inverse...
In this paper, we propose a novel hierarchical method for remote sensing image classification. The proposed approach integrates an explicit hierarchical graph-based classifier, which uses a quad-tree structure to model multiscale interactions, and a third order Markov mesh random field to deal with pixel wise contextual information in the same scale. The choice of a quad-tree and the third order Markov...
A novel approach to spatio-temporal saliency detection in video is proposed. Saliency computation is considered as an optimization problem that maximizes the energy of a fully-connected graphical model based on spatio-temporal feature distinctiveness. Each pixel in a video is modeled by a node, and the spatio-temporal feature distinctiveness between pixels by edges connecting the nodes in the graph...
The emergence of UHD video format induces larger screens and involves a wider stimulated visual angle. Therefore, its effect on visual attention can be questioned since it can impact quality assessment, metrics but also the whole chain of video processing and creation. Moreover, changes in visual attention from different viewing conditions challenge visual attention models. In this paper, we present...
In this study, we make use of brain activation data to investigate the perceptual plausibility of a visual and an auditory model for visual and auditory saliency in video processing. These models have already been successfully employed in a number of applications. In addition, we experiment with parameters, modifications and suitable fusion schemes. As part of this work, fMRI data from complex video...
While conventional synthesis dictionary learning approaches have demonstrated tremendous success in various pattern recognition problems, the dictionary pair learning, i.e., jointly learning an analysis dictionary and a synthesis dictionary is still an open problem. Furthermore, the performance of traditional supervised dictionary learning methods is often limited by the amount of labeled training...
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.