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Efficient and robust detection of humans has received great attention during the past few decades. This paper presents a two-staged approach for human detection in RGB-D images. As the traditional sliding window-based methods for target localization are often time-consuming, we propose to use the super-pixel method in depth data to efficiently locate the plausible head-top locations in the first stage...
Stereo correspondence is one of the most important steps in binocular stereovision. It consists feature point extraction and image matching. In order to solve the problems of bad anti-noise performance and low accuracy of image matching in Scale Invariant Feature Transform (SIFT) algorithm, an optimized matching method based on local feature algorithm with Speeded-up Robust Feature (SURF) is proposed...
In our previous work, we have applied ordinary linear regression equation to network anomaly detection. However, the performance of ordinary linear regression equation is susceptible to outliers. Unfortunately, it is almost impossible to obtain a “clean” traffic data set for ordinary regression model due to the burstiness of network traffic and the pervasive network attacks. In this paper, we make...
This paper considers the recovery of group sparse signals over a multi-agent network, where the measurements are subject to sparse errors. We first investigate the robust group LASSO model and its centralized algorithm based on the alternating direction method of multipliers (ADMM), which requires a central fusion center to compute a global row-support detector. To implement it in a decentralized...
Numerous trackers have been proposed in recent years with considerable success. But few trackers can cope with all scenarios without failures. It is very difficult to design a tracker robust enough to keep off tracking failure. As failure is inevitable, we propose a framework to correct tracker, verify failure, predict object position and re-detect object. The original model of the first frame is...
Simultaneous Localization and Mapping (SLAM) requires both rotation and scale invariant features. Few algorithms have been developed with rotation and scale invariant features with few limitations. Thus, an algorithm has been proposed to address rotation and scaling invariance. Proposed algorithm Harris-FAST interest point detector is a fusion of Harris and FAST interest point detectors. The detector...
Authors proved existence of uniformly most powerful invariant algorithm based on the t-test. Conducted study allowed to synthesize decision rule for detection of image features on 3×3 pixel patch was found. Simulation proved stability of the proposed feature point detection algorithm to change of mean value and standard deviation of background pixels' intensity. Versatility of detection algorithm...
Many image processing applications require to detect a known pattern buried under noise. While maximum correlation can be implemented efficiently using fast Fourier transforms, detection criteria that are robust to the presence of outliers are typically slower by several orders of magnitude. We derive the general expression of a robust detection criterion based on the theory of locally optimal detectors...
Effective detection of the feature points in images requires usage of detectors that produces similar results in variable observation conditions. Authors present a feature detector which is based on a uniformly most powerful invariant algorithm that uses t-test. The authors obtained equations that allow evaluating the effectiveness of the robust feature detector. Simulation proved the robustness (constant...
In this paper, we propose a keypoint selection scheme for SIFT and KAZE features and demonstrate their effectiveness in object characterization. The selection criterion rely on the detectability, distinctiveness and repeatability of the keypoints. These scores are combined to give a keypoint saliency score. The keypoints are ranked according to their saliency values and weak/irrelevant keypoints are...
Today's tape storage systems are widely used as a low-cost solution for data backup and archiving for the rapidly growing amount of digital information produced in various fields. Following the Information Storage Industry Consortium (INSIC) Roadmap [1], tape cartridge capacity continues to scale by doubling the capacity every two years. Developments in read channel technology are expected to play...
A well used approach for echo cancellation is the two-path method, where two adaptive filters in parallel are utilized. Typically, one filter is continuously updated, and when this filter is considered better adjusted to the echo-path than the other filter, the coefficients of the better adjusted filter is transferred to the other filter. When this transfer should occur is controlled by the transfer...
This paper proposes a new human detection method, which is robust to illumination change and does almost not confuse human with other objects even they have similar contours. This method is based on integration with two features: Higher-order Local Auto-Correlation (HLAC) features and Histograms of Oriented Gradients (HOG) features. HLAC features can give a broad pattern of gray scale image. The features...
This paper deals with robust fault detection and isolation using bond graph approach and linear filters. The bond graph tool is used to model the dynamic system and the uncertainties on the sensors and actuators. The same model is used to generate systematically the analytical redundancy relations and the thresholds. A specific form of digital linear filter is used to evaluate the residuals and to...
The importance of real-time speed estimation is undoubtedly significant for traveler information and traffic management systems. Unfortunately, the most common form of traffic detector, the single loop detector, is incapable of providing speed measurements. Analyzing the weakness of mean effective vehicle length (MEVL), typical effective vehicle length (TEVL) was introduced instead of MEVL using in...
One of the most challenging phenomena that can be observed in an ensemble of interacting agents is that of self-organisation, viz. emergent, collective behaviour, also known as synergy. The concept of synergy is well-known in the artificial intelligence community, in social science, and in management and economic sciences. The paradigm may be expressed by identifying an ensemble performance measure...
A new methodology has been developed for creating detection algorithms for the class of composite hypothesis testing problems. Rather than estimating unknown parameter values for each variate test value, as in the generalized likelihood ratio test, continuum fusion methods integrate an infinite number of optimal detectors, one for each parameter value. The final form of the algorithm depends on the...
Basically, detecting convex and concave points on the boundary of an object plays an important role in computer vision, object recognition and image understanding. In this paper a method that combines boundary and skeleton information for detecting these critical points is proposed. Specifically, the method is developed with the aim of obtaining high performance and efficiency, and producing a more...
Feature detectors are schemes that locate and describe points or regions of `interest' in an image. Today there are numerous machine vision applications needing efficient feature detectors that can work on Real-time; moreover, since this detection is one of the most time consuming tasks in several vision devices, the speed of the feature detection schemes severally affects the effectiveness of the...
Parallel adaptive filters have been proposed for echo cancellation to solve the dead-lock problem, occurring when the echo is detected as near-end speech after a severe echo-path change; causing the updating of the adaptive filter to halt. To control the parallel filters and monitor their performance, estimates of the filter deviation (i.e. the squared norm of the filter mismatch vector) are typically...
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