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Salient Object Detection (SOD) has received much attention from the research community due to its increasing applications in the areas such as object detection and recognition, image editing, image and video compression, video summarization and so on. Most of the SOD methods are proposed in literature presuming that the digital images in which salient objects is to be detected, are free from any kind...
In this paper we present a framework for the estimation of the pose of an object in 3D space: from the detection and subsequent recognition from a 3D point-cloud, to tracking in the 2D camera plane. The detection process proposes a way to remove redundant features, which leads to significant computational savings without affecting identification performance. The tracking process introduces a method...
The task of large-area visual monitoring for the protection of critical and public infrastructures calls for reliable automated visual surveillance systems. Reliability in this context implies that a high detection accuracy of critical events shall be maintained independent from observation conditions, appearance and pose variations of observed objects (persons, cars), while accomplishing a low-rate...
In this paper, a region-based moving object detection based on hu moments is concerned. Firstly, the feasibility analysis of hu moments in moving object detection is performed. Then a model of hu moments in moving object detection is presented and the performances are evaluated. The experiment results show that the hu moments can eliminate the large amount of noise caused by traditional Single Gaussian...
This paper presents an activity detection system using dendrite threshold logic neuron models. This method generates a dendrite weight matrix from the background image and detect the changes in the subsequent images through the trained neuron outputs. Using only one layer of dendrite neuron cells with simplistic threshold logic cells, an accuracy of 98% is reported in realistic imaging conditions...
In this paper we propose an efficient approach for circular shape target recovery. The method makes use of the conterminous set of edge segments, or contour segments, instead of the huge edge points as traditional detectors do. First, the proposed approach computes the contour in a given image, which is then converted into contour segments at high curvature points. Then, by calculating the reinforcement...
In this research, we focus low illumination video image of "below 1 lux" obtained by normal type video camera, and we consider the method of image correction for moving-object detection by inter-frame differencing. The method of this research is the combination of gamma correction and denoising as the preparation of inter-frame differencing. By such method, the moving-object detection which...
This paper examines the 50-year old problem of the properties of the optimum “waveform-mismatched filter” pair. In particular, it is demonstrated that the conjecture made in [5], [6] that for an arbitrary area in the range-Doppler frequency plane occupied by clutter, the optimum waveform calculated for one target Doppler frequency is also optimum for other target Doppler frequencies, is in general...
In this paper, an Adaptive Median Constant False Alarm Rate (AMCFAR) and multi-frame post detection integration algorithm is proposed for effective real time automatic target detection of boat-generated acoustic signals, in which, an observation space is created by sampling and dividing input analog acoustic signal into multiple frames and each frame is transformed into the frequency domain. In the...
Through the analysis of common moving target detecting algorithms, this paper proposes a moving target detecting algorithm based on Susan edge detection and frame difference. It detects the edge information of current frame image by Susan operator, then taking a differential operation between the current frame and the next frame image to get the outline of moving target. Finally, it extracts the target...
Broadband high-resolution radar target echo is irradiated with multiple scattering centers. Echo distribute on each target range cell expansion. Signal is weak and decentralized energy distribution more, The noise power and the distribution of each unit are essentially the same distance. This makes the unit at the same distance, lower SNR, the effective signal detection becoming more difficult. Therefore,...
In recent years emergence of many intelligent autonomous systems are possible due to the tremendous advancement of various technologies like computer vision and automation and control engineering with sensor technology. One such intelligent system is autonomous underwater vehicle (AUV) for ocean floor mapping by SONAR technology. Success of this autonomous smart and precise intelligent system depends...
This paper presents a new and efficient approach for automatic pedestrian detection in infrared images. The approach consists of three steps; initially, background subtraction model designed based on the input image intensity properties of target and background region to suppress the noise in image. Secondly, order statistics filter is applied on the background suppressed image to enhance the target...
We proposed an efficient method to detect object and the boundary of the object. The object detection is done after the subtraction between background and object with background in gray scale wit threshold, which is generated from the normal distribution curve fitted histogram. In most of the existing methods for binary scale conversion and detection of object only one threshold used, here we used...
Moving objects often contain almost important information for surveillance videos, traffic monitoring, human motion capture etc. Background subtraction methods are widely exploited for moving object detection in videos in many applications. Moving object segmentation is the application in video processing. Segmentation helps in detecting various features of moving objects for further video/image processing...
In current scenario, the need of surveillance applications, technological improvements, and the numbers of active real-time surveillance systems are increasing continuously throughout the world. In this research work, we have presented a background subtraction based scheme for moving object detection in video frames. The proposed scheme has a strong potential for applications in consumer electronics...
In the field of infrared remote sensing, the problem of IR small target detection is still an important component part. Concerning infrared dim small target (IRDST) detection, firstly the infrared image is processed with DWT method to get the wavelet coefficients image, but the distribution characteristics, such as scales, frequencies, orientations of wavelet coefficients in different sub-bands are...
Almost every computer vision applications used background subtraction method to detect moving objects from video sequence. Moving object detection and tracking is generally the first step in many applications such as face detection, traffic surveillance, object recognition, detection of unattended bags, people counting etc. Background modeling is very useful and effective method for locating objects...
This study aims to develop a system to detect traffic conditions by using computer vision. The system detects the presence of cars, motorcycles and pedestrians in the traffic; and also calculates the detected objects. The system detects the objects by using feature extraction method that is Histogram Oriented Gradient (HOG) and using linear Support Vector Machine (SVM) classifier. The system calculates...
Within the field of automated video analysis, detection of moving objects remains a challenging task due to the presence of dynamic background and camera motion. Dynamic scenes contain some moving objects such as trees jiggling slightly and water flowing irregularly. In this paper, we present an algorithm to address the problem of dynamic background, which employs spatio-temporal context and background...
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