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.
This paper proposes a new spatio-temporal appearance feature named Phasic Maximal and Local Maximal Occurrence (PM-LOMO) representation for video-based person re-identification. To perform temporal alignment of the sequence, we selected the optimal period of walking cycle and divide frames into several phases based on the extreme points of the sequence's Flow Energy Profile (FEP). To describe the...
Web browsing is an activity that billions of mobile users perform on a daily basis. Battery life is a primary concern to many mobile users who often find their phone has died at most inconvenient times. The heterogeneous multi-core architecture is a solution for energy-efficient processing. However, the current mobile web browsers rely on the operating system to exploit the underlying hardware, which...
Blur is certainly one of the most encountered and the most annoying degradation types in image. It is due to several causes such as compression, motion, filtering and so on. In order to estimate the quality of this kind of degraded images, several metrics have been proposed in the literature. In this paper, we focus our attention on stereoscopic images and we propose a fusion-based blind stereoscopic...
The registration of remote sensing images has been often a necessary step for further analyses of images taken at different times, different viewing geometry or with different sensors. For this task there exists many approaches. This paper focuses on the feature-based category of image registration methods. Particularly, we propose an improvement of the SURF algorithm on the point matching step. Indeed,...
Over the past decade, numerous systems have been proposed to detect and subsequently prevent or mitigate security vulnerabilities. However, many existing intrusion or anomaly detection solutions are limited to a subset of the traffic due to scalability issues, hence failing to operate at line-rate on large, high-speed datacentre networks. In this paper, we present a two-level solution for anomaly...
We propose an active exposure control method to improve the robustness of visual odometry in HDR (high dynamic range) environments. Our method evaluates the proper exposure time by maximizing a robust gradient-based image quality metric. The optimization is achieved by exploiting the photometric response function of the camera. Our exposure control method is evaluated in different real world environments...
As a kind of popular problem in machine learning, multi-instance task has been researched by means of many classical methods, such as kNN, SVM, etc. For kNN classification, its performance on traditional task can be boosted by metric learning, which seeks for a data-dependent metric to make similar examples closer and separate dissimilar examples by a margin. It is a challenge to define distance between...
Traditional approaches to simultaneous localization and mapping (SLAM) rely on low-level geometric features such as points, lines, and planes. They are unable to assign semantic labels to landmarks observed in the environment. Furthermore, loop closure recognition based on low-level features is often viewpoint-dependent and subject to failure in ambiguous or repetitive environments. On the other hand,...
In this paper, we propose a novel no reference (NR) quality assessment metric for stereoscopic images by statistical features. First, we calculate the luminance map through the local normalization, which is further used to extract the statistic luminance features. Second, we predict the disparity map of the stereoscopic image, which is further combined with the corresponding left and right views to...
Idioms are well known for posing problems to non-native speakers, let alone machines. A failure to identify idioms often leads to unnatural, even hilarious outputs. This paper investigates the treatment of idioms in state-of-the art SMT systems involving English and Croatian. First we introduce the concept of idioms. Then we construct three short stories abundant with idioms per each language, and...
In this paper, a monocular vision measurement method based on rotating lens is proposed. A special optical lens is placed between the target and the camera, which causes light refraction during the measurement process. By analyzing images taken after different light refraction, the 3D coordinates of the target can be obtained. Using this method, 3D measurement of the full field can be completed with...
In this paper a no-reference image quality assessment (IQA) metric for DIBR-synthesized images is proposed. Sparsity based features of morphologically decomposed image subbands are used to estimate distortion level in images. A General regression neural network is utilized to calculate quality score. The performance is evaluated using publicly available IRCCyN/IVC DIBR image database. Experimental...
In this study, the motion blur caused by the variable speed egomotion of camera is deblurred using multiple image frames and the obtained results are compared based on the detection performance of corner features. A linear, uniform motion blur data set is collected which is suitable for testing the multi-image deblurring method. The proposed method is tested on the dataset together with two baseline...
As a fundamental task in automated video surveillance, person re-identification, which has received increasing attention in recent years, aims to match people across non-overlapping camera views in a multi-camera surveillance system. It has been reported that KISS metric learning has been followed by most of the previous supervised work because of its state of the art performance for person re-identification...
In this paper we use a Deep Neural Network (DNN) trained on data collected from the visual media-sharing social platform Instagram account of a popular Indian lifestyle magazine to predict the popularity of future posts. This predicted popularity of the post can be used to decide advertising rates and measure performance metrics important for publishing strategy decisions. The DNN primarily uses growth...
Text mining discover and extract useful information from documents, whenever increase the size and number documents leads to redouble features. The huge features for the documents adds challenge to text mining called high dimension. The aim of this proposed study is minimize the high dimension of the documents, and improve Arabic text mining using clustering. In order to achieve this goal, we propose...
While accurate tumor delineation in FDG-PET is a vital task, noisy and blurring imaging system makes it a challenging work. In this paper, we propose to address this issue using the theory of belief functions, a powerful tool for modeling and reasoning with uncertain and/or imprecise information. An automatic segmentation method based on clustering is developed in 3-D, where, different from available...
The human visual perception is a layered progressive process that brain assimilates visual information gradually, from primary information, structural information to detailed information. Recently, the visual primitives (atoms in the dictionary) extracted by sparse representation have been shown to be highly related to the layered progressive process of human visual perception. In this paper, the...
Various techniques have been proposed to detect smells in spreadsheets, which are susceptible to errors. These techniques typically detect spreadsheet smells through a mechanism based on a fixed set of patterns or metric thresholds. Unlike conventional programs, tabulation styles vary greatly across spreadsheets. Smell detection based on fixed patterns or metric thresholds, which are insensitive to...
Preprocessors are a common way to implement variability in software. They are used in numerous software systems, such as operating systems and databases. Due to the ability of preprocessors to enable and disable code fragments, not all parts of the program are active at the same time. Thus, programmers and tools need to handle the interactions resulting from annotations in the program. With our Eclipse-based...
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.