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 research proposes a reliable machine learning based computational solution for human detection. The proposed model is specifically applicable for illumination-variant natural scenes in big data video frames. In order to solve the illumination variation problem, a new feature set is formed by extracting features using histogram of gradients (HoG) and linear phase quantization (LPQ) techniques,...
Wireless Sensor Network (WSN) has recently emerged as a new widely used technology. However, the deployment of such networks has reported high rates of failures. Due to resource constraints of sensor nodes, the design of efficient failure detection techniques has become a very challenging issue. Already proposed WSN fault detection protocols have reported either a high number of false suspicions,...
The design of a four-port scalar reflectometer operating at center frequency 2.4 GHz is presented in this paper. The proposed reflectometer is constructed from two 10 dB branch-line couplers, which are produced in microstrip line technique. Parameters of the realized device are in good agreement with simulation results. Directivity of the two couplers is over 22 dB at the center frequency. The reflection...
We propose a robust real-time person detection system, which aims to serve as solid foundation for developing solutions at an elevated level of reliability. Our belief is that clever handling of input data correlated with efficacious training algorithms are key for obtaining top performance. We introduce a comprehensive training method based on random sampling that compiles optimal classifiers with...
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...
In surveillance and scene awareness applications using power-constrained or battery-powered equipment, performance characteristics of processing hardware must be considered. We describe a novel framework for moving processing platform selection from a single design-time choice to a continuous run-time one, greatly increasing flexibility and responsiveness. Using Histogram of Oriented Gradients (HOG)...
This paper addresses the problem of person re-identification and its application to a real world scenario. We introduce a retrieval system that helps a human operator in browsing a video content. This system is designed for determining whether a given person of interest has already appeared over a network of cameras. In contrast to most of state of the art approaches we do not focus on searching the...
Green Light Optimized Speed Advisory (GLOSA) systems have been shown to be able to reduce both CO2 emissions and fuel consumption by giving drivers speed recommendations when approaching a traffic light. For the system to reach its maximum potential, is is necessary to properly predict all different types of traffic lights, that is, also adaptive traffic lights where signals may change with lead times...
Since the beginning of the 21th century, with the continuous development of information technology, it has been the difficulty and hotpot in understanding field to study and analyze sports videos with computer technology. Because soccer videos have a broad mass background, it is more valuable to research on it. At present, there are many researches based on trajectory information of players or balls...
As process technology scales, electronic devices become more susceptible to transient faults induced by radiation. Symptom-based detection techniques provide promising low-cost and effective solutions, but could hardly catch faults that produce silent data corruptions (SDCs). Identifying and understanding instructions that cause SDCs is crucial to the development of program-level detectors. This paper...
This paper describes a new approach to detect and track maritime objects in real time. The approach particularly addresses the highly dynamic maritime environment, panning cameras, target scale changes, and operates on both visible and thermal imagery. Object detection is based on agglomerative clustering of temporally stable features. Object extents are first determined based on persistence of detected...
In this work, we present a comparative evaluation of various ‘tracking-by-detection’ approaches on public datasets. The work investigates popular sequential Monte Carlo and template ensemble based trackers coupled with relevant visual people detectors with emphasis on exhibited performance variation depending on tracker-detector choice. Extensive experimental results are provided on public dataset...
In this paper, a Binary Robust Invariant Scalable Keypoints (BRISK) based detection is utilized to facilitate the flying unmanned aerial vehicle (UAV) localization within its autonomous landing on the runway. Specifically, two target detection algorithms are proposed and developed as the BRISK-supported approach. Dataset of images and differential GPS are recorded by a ground stereo vision guidance...
With the development of computer vision technology, many researches about feature detectors and descriptors have been published in the last decades. In order to explore what kind of approaches are appropriate for unmanned aerial vehicle (UAV) onboard video processing, the popular feature detectors and descriptors are analyzed and combined with each other. Three practical videos captured in indoor...
Anomaly detection systems rely on machine learning techniques to model the normal behavior of the system. This model is used during operation to detect anomalies due to attacks or design faults. Ensemble methods have been used to improve the overall detection accuracy by combining the outputs of several accurate and diverse models. Existing Boolean combination techniques either require an exponential...
System call analysis is a behavioral malware detection technique that is popular due to its promising detection results and ease of implementation. This study describes a system that uses system call analysis to detect malware that evade traditional defenses. The system monitors executing processes to identify compromised hosts in production environments. Experimental results compare the effectiveness...
This paper presents a feature guided multi-window area-based matching method for urban remote sensing stereo pairs. The method achieves the goal that producing dense disparity maps for urban remote sensing stereo pairs. The proposed method can be divided into four stages: feature-based matching, edge support region extraction, area-based matching and post-processing. The point feature matching is...
Scale-space corner detection (SSCD) has been drawing much attention in the past. Multi-scale corner detection (MSCD), which recognizes corners only at several scales, can be treated as a fast implementation of SSCD. In this paper, a new MSCD algorithm is proposed, which is based on an arithmetic mean (AM) of the k-cosine curvature values respectively computed at three scales. Compared to the existing...
In many agricultural applications, PolSAR data are widely used because they can be decomposed into various scattering components, which can be of help in observing the characteristics of agricultural areas. Recently, studies have been conducted to find suitable polarimetric parameters for specific applications. This paper tried to find appropriate polarimetric parameters for line extraction from agricultural...
We propose a novel approach to segment hand regions in egocentric video that requires no manual labeling of training samples. The user wearing a head-mounted camera is prompted to perform a simple gesture during an initial calibration step. A combination of color and motion analysis that exploits knowledge of the expected gesture is applied on the calibration video frames to automatically label hand...
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.