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.
Visual motion perception in biological vision systems is typically modeled via a set of elementary motion detectors (EMDs) forming a spatially distributed network. This paper addresses the problem of estimating the weights of such an EMD construct from a linear combination of their output signals. This challenge arises in e.g. mathematical modeling of animal motion perception. In particular, the spatial...
In this paper, an online visual object tracking algorithm based on the discriminative sparse representation framework with supervised learning is proposed. Different from the generative sparse representation based tracking algorithms, the proposed method casts the tracking problem into a binary classification task. A linear classifier is embedded into the sparse representation model by incorporating...
The paper proposes CONSIFT descriptors which are the rotation-variant modification of SIFT (primarily for affine-invariant keypoints). CONSIFT of a keypoint K is its SIFT computed relatively to the orientation defined by the location of another keypoint L (and concatenated with similarly computed SIFT for keypoint L relatively to the location of K). It is additionally recommended that K and L are...
Fuzzy Cognitive Map (FCM) is a tool for modeling human beings' causal knowledge. As compared to many other knowledge models, it is much easier for domain experts to understand. However, domain experts with no computer science expertise still have difficulties in express their knowledge into FCM directly. Majority of the FCM applications in recent years are reported by computing experts in collaboration...
In allusion to similarity calculation difficulty caused by high maintenance of image data, this paper introduces sparse principal component algorithm to figure out embedded subspace after dimensionality reduction of image visual words on the basis of traditional spectral hashing image index method so that image high-dimension index results can be explained overall. This method is called sparse spectral...
Content-based image retrieval (CBIR) is the application of computer vision techniques to the image retrieval problem. There are two main content-based image retrieval paradigms: one based on visual queries, referred to as query-by-visual-example (QBVE), and the other based on semantic content, denoted as semantic retrieval. In this paper, we compare these two kinds of retrieval systems by conducting...
Human activity recognition is a crucial area of computer vision research and applications. The goal of human activity recognition aims to automatically analyze and interpret ongoing events and their context from video data. Recently, the bag of visual words (BoVW) approach has been widely applied for human action recognition. Generally, a representative corpus of videos is used to build the Visual...
Food-related photos have become increasingly very popular, due to social networks, food recommendation and dietary assessment systems. Reliable annotation is essential in those systems, but user-contributed tags are often non-informative and inconsistent, and unconstrained automatic food recognition still has relatively low accuracy. Most works focus on exploiting only the visual content while ignoring...
This paper presents a novel method for visualizing vectors of fuzzy numbers. The proposed approach is an extension of the standard polar area diagram and can be applied to a single uncertain vector or a fuzzy weighted graph with vectors of fuzzy attributes on the vertices and/or edges. The resulting diagrams are intuitive to understand and do not require an extensive background in fuzzy set theory...
As scientific workflows are increasingly deployed in clouds, a myriad of studies have been conducted-including the development of workflow execution systems and scheduling/resource-management algorithms-for optimizing the execution of these workflows. However, the efficacy of most, if not all, of these previous works is limited by the original design and structure of workflow, i.e., Sequential code...
This paper presents a new concept of assessing image quality. It is based on support vector regression (SVR) fusion. Despite the variety of the proposed IQM measures, no efficient and sufficient measure gives good performance over different distortions. Motivated by this problem, a new measure for No reference Image Quality Assessment Based on SVR Fusion (NR BSVRF) is constituted. First, five recent...
Recently the inverted generational distance (IGD) measure has been frequently used for performance evaluation of evolutionary multi-objective optimization (EMO) algorithms on many-objective problems. When the IGD measure is used to evaluate an obtained solution set of a many-objective problem, we have to specify a set of reference points as an approximation of the Pareto front. The IGD measure is...
In this work we propose a new key frame extraction method based on SIFT local features. We extracted feature vectors from a carefully selected group of frames from a video shot, analyzing those vectors to eliminate near duplicate key frames, helping to keep a compact set. Moreover, as the key frame extraction is based on local features, it keeps frames latent semantics and, therefore, helps to keep...
In this paper we propose a robust sparse based visual tracking method by exploiting local representations in a particle filter framework. We construct a Multi-level Local Dictionary which consists of positive templates and negative templates for discriminative model, Which divide the positive and negative dictionary into two levels called static templates and dynamic templates, respectively, thus...
The identification of critical nodes is relevant to determine the structural vulnerability of an Electric Power System. In this article, centrality indices from the area of complex networks analysis are adapted to identify nodes and lines that result critical for the transmission of energy. The centrality indices are calculated in each sub-graph, to rapidly assess the structural vulnerability of the...
This paper introduces the framework of mobile Computer Music interfaces within the context of Human Computer Interaction (HCI). It examines the unique problems posed by the use of computers by composers and performers of music. It emphasizes on the new various interfacing protocols, metaphors and paradigms that apply HCI design methodologies on the world of music, producing special modules like: performance...
Image secret sharing is an important research topic in the field of information security. Compared to a lot of digital information, images are favored in the network due to having a vivid, visual characteristics. However, most image secret sharing schemes without considering the characteristics of the image just regard the image as a series of general data and directly using the common secret sharing...
This paper presents a methodology based on image processing, circuit theory and state variables to estimate the voltage profile along an electrical grid with RLC frequency dependent elements. Numerical techniques are used to obtain the dynamic solutions of EMTP, Z transform and Laplace transform of an electric grid. Finally, based on the theoretical solution of an infinite resistive network, the matrix...
Nearest-neighbor (NN) methods are among the most popular and highly effective techniques used in pattern recognition tasks. However, these methods have several drawbacks that impair their performance in large scale problems and noisy data sets. Some of these disadvantages includes its high storage requirements, its sensitivity to noisy instances, and the computational cost for estimating the distance...
In this paper, we propose an approach of following a visual path for humanoid navigation. The problem consists in computing appropriate robot velocities for the humanoid walking task from the visual data shared between the current robot view and a set of target images. Two types of visual controllers are evaluated: a position-based scheme and an image-based scheme. Both of them rely on the estimation...
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.