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Research efforts have been devoted to extraction and visualization of vortices in an unsteady (turbulent) flow. Characterizing the behaviors of the flow, vortices are identifiable as regions using a vortex detector known as the lambda2-criterion. Isosurface visualization renders vortex regions based on a chosen isovalue. However, it is highly challenging to choose one isovalue suitable for visualizing...
In many real world applications, human analysts are not only interested in the detected anomalies but are also interested in the reasons behind why they were flagged as anomalous. However, existing anomaly detectors provide the analysts with no information about what caused the anomalies. A sequential feature explanation(SFE) of a detected data point is an ordered sequence of features which are presented...
In this paper, we propose a new method to automatically extract the main structure (fuselage and wings) of straight wing aircraft in photographic images using line clustering. We exploit the location, length and orientation features (parallel constraint) of line segments to group them into line clusters. The different line clusters correspond to the different structure of straight wing aircraft, and...
In order to address the high transmission bandwidth requirement of an Internet-of-Video-Things (IoVT), an object-based on-line video summarization algorithm is proposed to summarize the captured video information at the sensor nodes before being transmitted to the server. It is composed of two stages: intra-view and inter-view stages. In the intra-view stage, human object detector is employed with...
Metamorphic malware are able to change their appearance to evade detection by traditional anti-malware software. One of the ways to help mitigate the threat of new metamorphic malware is to determine their origins, i.e., the families to which they belong. This type of metamorphic malware analysis is not typically handled by commercial software. Moreover, existing works rely on analyzing the op-code...
While Optical Character Recognition (OCR) can be considered as a solved problem, text detection and recognition in real scene images is still extremely challenging and remains an open problem. Due to the wide variety of text appearances in real scenes, such as variations in font, size, color, orientation, partial occlusions, different distortions and illumination conditions, current results of both...
Humans are the most common mobile obstacles for an office robot. A robust human detector usually plays important roles in robots' perception phase. Especially, Tasks like dynamic path planning and obstacle avoidance have to employ such a detector to help make real-time decisions. Thus, an efficient human detector is meaningful for office robots. However, while deep learning based detectors are not...
Local feature matching is one of the most fundamental issues in computer vision. Hierarchical agglomerative clustering (HAC) has been effectively used to distinguish inliers from outliers. The drawback of HAC is its large computational complexity which increases rapidly as the number of feature correspondences increases. To overcome this drawback, this paper proposes a region-constrained feature matching...
This paper presents a method to deal with the multi-body segmentation problem using a set of 2D points matches between two views. The key feature of our approach is the explicit inclusion of a higher semantic information as given by general purpose object detectors that boost the segmentation of the moving objects. In the classical formulation of the problem, only 2D matched points between views are...
A new approach to autonomously detect and track moving objects in a video captured by a moving camera from a UAV in real-time is proposed in this paper. The introduced approach replaces the need for a human operator to perform video analytics by autonomously detecting moving objects and clustering them for tracking purposes. The effectiveness of the introduced approach is tested on the footage taken...
In this paper, we study the problem of ‘test-driving’ a detector, i.e. allowing a human user to get a quick sense of how well the detector generalizes to their specific requirement. To this end, we present the first system that estimates detector performance interactively without extensive ground truthing using a human in the loop. We approach this as a problem of estimating proportions and show that...
This paper introduces an automatic method for licenses plate detection that using local corners points features, clustering and some properties of license plate. Licenses plates are rich corner point's area that can be used with some properties of license plate to locate licenses plate location. The algorithm has four stages; firstly, the quality of image is improved via preprocessing operations....
The ATLAS detector operated very successfully at the LHC Run 1 data taking period collecting a large number of events used for different physics analyses, such as the ones leading to the discovery of the Higgs boson as well as for the search for beyond the Standard Model physics. In the main search channels related to the finding of the Higgs, the ATLAS calorimeter system played a major role by measuring...
In this paper, an improved implicit shape model is presented for on-road vehicle and pedestrian detection. Implicit shape model (ISM) is widely used for object detection and categorization. The training of ISM usually consists of three components: interest point detector, local feature descriptor, codebook generation. We evaluate six common interest point detectors to determine the best detector for...
It is important for mobile robot to match features from scenes under wide baseline views. Wide baseline matching is one of the difficult problems in feature matching because large variation between the image appearances occurs due to illumination and viewpoints, especially on non-planar and less-textured scenes. In this paper we propose a method of feature matching under large separate views, which...
Hardware platforms with limited processing power are often incapable of running dense stereo analysis algorithms at acceptable speed. Sparse algorithms provide an alternative but generally lack in accuracy. To overcome this predicament, we present an efficient sparse stereo analysis algorithm that applies a dense consistency check, leading to accurate matching results. We further improve matching...
Several methods have been developed in order to recognize a location from an image. Early methods use appearance based matching, but they usually failed to handle occlusion. Recently, some methods using feature based matching have been developed. They are more robust and faster than the appearance based, but processing time and memory usage are still aspects which can be improved further.
In order to search for rare processes, all four Large Hadron Collider experiments have to use advanced triggering methods for selecting and recording the events of interest. For this reason the understanding and evaluation of the trigger performance is one of the most crucial parts of any physics analysis. This paper summarizes the status of some of the software projects in the ATLAS Collaboration...
This paper presents a method for counting people in a scene by establishing a mapping between some scene features and the number of people avoiding the complex foreground detection problem. The method is based on the use of SURF features and of an ∈-SVR regressor to provide an estimate of this count. The algorithm takes specifically into account problems due to partial occlusions and to perspective.
This paper presents a novel method to count people for video surveillance applications. Methods in the literature either follow a direct approach, by first detecting people and then counting them, or an indirect approach, by establishing a relation between some easily detectable scene features and the estimated number of people. The indirect approach is considerably more robust, but it is not easy...
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