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There are two practical problems in image fusion by using Dempster-Shafer (DS) combination rule: one is the classical DS rule involves counter-intuitive behaviors when deal with high conflict information, another is that it is difficult to determine the basic mass function of pixels. A method of image fusion with modified DS evidence theory is proposed to recognize small infrared targets in image...
In multiple moving object detection, the connection between objects and shadow always leads to the failure of object detection. To solve this problem, a new object extraction algorithm using level set is proposed and applied to detect moving vehicle in intelligent monitoring of motorway. Moving information is extracted via symmetrical difference and used in the velocity function of level set. After...
High quality motion-adaptive de-interlacing calls for high quality spatial interpolation that can generate smooth object edges without jaggy effects. In this paper, we present a hierarchical edge-directed interpolation, where the edge detection not only covers very wide range of angles but also provides high resolution edge vectors. In addition, the hierarchical architecture makes it highly efficient...
In this paper we present an adaptive multi-camera system for real time object detection able to efficiently adjust the computational requirements of video processing blocks to the available processing power and the activity of the scene. The system is based on a two level adaptation strategy that works at local and at global level. Object detection is based on a Gaussian mixtures model background...
In the Dynamic Background, due to the changes of background, it is difficult to effectively extract moving target. This paper adopts the gray projection matching algorithms to transform dynamic background into static background and then extracts the moving target using frame difference method. Meanwhile, according to the extracted position coordinates, the deflection angle of moving target between...
Images of folding process was collected and on-line detection of folding dislocations is explored using characteristic points in these images, which reduces the computation time. First, determine the dislocation type through characteristic points in the images of a folding process. Then, through calibration the corresponding dislocation bias for the detected type of folding dislocation can be obtained...
The interest points detection of foreground (moving) objects in videostreams is one of the key step in such applications as: path tracking, computer vision etc. The points of interest should have several features as: few interest points in each moving object, they should be well localized. This conditions are fulfilled by corners of moving objects. The requirements which desirable for a corner detectors...
The proposed classifier is a novel skin detector that outperforms most of the existing approaches by dropping most of the non-skin pixels in its earlier stages of weak classifiers. Only the pixels with maximum skin likelihood are processed in later adaptive classifier. Parametric background modelling and validation based online training significantly improves the robustness of the whole classifier...
Object detection is a vital task in several emerging applications, requiring real-time detection frame-rate and low energy consumption for use in embedded and mobile devices. This paper proposes a hardware-based, depth-directed search method for reducing the search space involved in object detection, resulting in significant speed-ups and energy savings. The proposed architecture utilizes the disparity...
Detecting people carrying objects is a commonly formulated problem as a first step to monitor interactions between people and objects. Recent work relies on a precise foreground object segmentation, which is often difficult to achieve in video surveillance sequences due to a bad contrast of the foreground objects with the scene background, abrupt changing light conditions and small camera vibrations...
Illumination changes present challenging problems to video surveillance algorithms tasked with identifying and tracking objects. Illumination changes can drastically alter the appearance of a scene, causing truly salient features to be lost amid otherwise stable background. We describe an illumination change compensation method that identifies large, stable, chromatically distinct background features-called...
We describe a system for localizing and deblurring motion-blurred 2D barcodes. Previous work on barcode detection and deblurring has mainly focused on 1D barcodes, and has employed traditional image acquisition which is not robust to motion blur. Our solution is based on coded exposure imaging which, as we show, enables well-posed de-convolution and decoding over a wider range of velocities. To serve...
This paper proposes a novel computational framework for saliency detection, which integrates the saliency map computation and proto-objects detection. The proto-objects are detected based on the saliency map using latent topic model. The detected proto-objects are then utilized to improve the saliency map computation. Extensive experiments are performed on two publicly available datasets. The experimental...
This paper presents a new method for accurate skin detection. Skin detection techniques are used in various image and video processing applications, such as image categorization, face detection and tracking and, more recently, in selective image enhancement for digital TV products. The proposed method achieves high accuracy using a combination of color information and pseudo-morphological processing,...
In recent years, the watershed line has emerged as a primary tool of mathematical morphology for image segmentation, though the application of watershed algorithms to an image is often disappointing. Based on the mathematical morphology, this paper develops a general purpose watershed segmentation algorithm used for the automatic segmentation in regions of pedestrians of infrared image. The approaches...
Designing static object detection systems that are able to incorporate user interaction conveys a great benefit in many surveillance applications, since some correctly detected static objects can be considered to have no interest by a human operator. Interactive systems allow the user to include these decisions into the system, making automated surveillance systems more attractive and comfortable...
Detecting static objects in video sequences has a high relevance in many surveillance scenarios like airports and railwaystations. In this paper we propose a system for the detection of static objects in crowded scenes that, based on the detection of two background models learning at different rates, classifies pixels with the help of a finite-state machine. The background is modelled by two mixtures...
We present the Video Graph-Shifts (VGS) approach for efficiently incorporating temporal consistency into MRF energy minimization for multi-class video object segmentation. In contrast to previous methods, our dynamic temporal links avoid the computational overhead of using a fully connected spatiotemporal MRF, while still being able to deal with the uncertainties of the exact inter-frame pixel correspondence...
The quality achieved by simply scaling a sports video to the limited display resolution of a mobile device is often insufficient. As a consequence, small details like the ball or lines on the playing field become unrecognizable. In this paper, we present a novel approach to analyzing court-based ball sports videos. We have developed new techniques to distinguish actual playing frames, to detect players,...
In order to detect traffic sign effectively and quickly, firstly, this paper firstly discriminates the maximum and minimum values of the color-components R, G and B, and then ignores pixels having little color similarity with traffic sign. Secondly, it regards the points of RGB space as color eigenvector and calculates the cosine value of included angle of vectors to discriminate color similarity...
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