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The complexity of hand function is such that most existing upper limb rehabilitation robotic devices use only simplified hand interfaces. This is in contrast to the importance of the hand in regaining function after neurological injury. Computer vision technology has been used to identify hand posture in the field of Human Computer Interaction, but this approach has not been translated to the rehabilitation...
In this work, a pedestrian detection method based on adaptive boosting is proposed. The proposed method works on still images. The features utilized in the work are derived from Haar-like templates. An Adaboost classifier is utilized for both feature selection and classification. To show the effectiveness of the proposed algorithm, the system is trained by using Nicta Pedestrian Dataset and tested...
This paper proposes an new algrithem framework for video based vehicle âtailgate' behavior detection in urban road junction. Based on the road traffic regualtion about the illegal parking behavior definition, the author proposes traffic lights signal monitor, vehicle tracking and road conjestion detection algrithems in the real time video analyse. The measured parameters including vehicles' trojactory,...
Single image haze removal (or de-haze) using dark channel prior model is effective when there exists a dark channel within the image. So for the images which do not meet the dark channel prior, the haze removal result may appear light pollution, cross-color. In this paper, we propose an algorithm to judge whether a single image meets the dark channel prior, and for the image that fails to meet the...
Optical flow is one of the tools for video content analysis (VCA). The optical flow involves a gradient coprocessor as preprocessing to estimate partial derivative. The gradient processor consists of kernels (masks) to convolute each pixel of image sequences. In hardware implementation of the gradient into FPGA, a multiply accumulate (MAC) is an important technique that is useful for reducing the...
For intelligent video monitor system, how to detect the moving target accurately is a key problem needed to be solved. The problem is more serious when background is complex. This paper uses a method based on code book to segment the foreground and background to detect the moving targets under complex background. This method uses the threshold of the color distortion of and brightness distortion....
This paper proposes a novel fast dehazing method based on dark channel prior. The dark channel prior is the phenomenon about normal outdoor images containing at least one low energy pixel around a block among three channels. It helps roughly estimating the air mediums thickness, which decreases the scene transmission. We propose a variation of optical model whose single atmospheric attenuation coefficient...
The process of repairing the damaged area or to remove the specific areas in a video is known as video inpainting. To deal with this kind of problems, not only a robust image inpainting algorithm is used, but also a technique of structure generation is used to fill-in the missing parts of a video sequence taken from a static camera. Most of the automatic techniques of video inpainting are computationally...
Most image retargeting algorithms rely heavily on valid saliency map detection to proceed. But the inefficiency of high quality saliency map detection severely restricts applications of these image retargeting methods. In this paper, we describe a stochastic algorithm for efficient context-aware saliency map detection. Our method is a multiple level saliency map detection algorithm which integrates...
Biological vision systems use saliency-based visual attention mechanisms to limit higher-level vision processing on the most visually-salient subsets of an input image. Among several computational models that capture the visual-saliency in biological system, an information theoretic AIM(Attention based on Information Maximization) algorithm has been demonstrated to predict human gaze patterns better...
The demand for high quality depth maps from stereo and multi-camera videos increases constantly. The main application for these depth maps is rendering new perspectives of the captured scene by means of Depth Image Based Rendering (DIBR). Accurate depth maps are the linchpin of DIBR. On the basis of a four-camera set-up, we show that combining hybrid recursive matching with motion estimation, cross...
To satisfy the demand of the real-time computer vision system, a method of camera calibration was analysed. According to the camera model from OpenCV(Intel Open Source Computer Vision Library), with radial aberration and tangential aberration considered, Zhang's arithmetic of camera calibration was applied. As the experimental result showed, the arithmetic exerted OpenCV library function at a great...
Patch cloud based multi-view stereo methods have proven to be an accurate and scalable approach for scene reconstruction. Their applicability, however, is limited due to the semi-dense nature of their reconstruction. We propose a method to generate a dense depth map from a patch cloud by assuming a planar surface model for non-reconstructed areas. We use local evidence to estimate the best fitting...
The vanishing point can be defined as a point generated by converged perspective lines, which are parallel in the real world. We propose a novel algorithm to detect the vanishing point in various images in real-time. The proposed algorithm unfolds into three steps. In the first step, we introduce the Local Dominant Orientation Signature (LDOS) descriptor to extract structural feature of an image....
We propose a new approach to motion segmentation that is based on auto-generated strokes. The novelty of the approach is twofold. First, inspired by recent work of other researchers we formulate the problem as that of interactive segmentation. Instead of inputting the strokes by the user, the strokes in our approach are auto-generated. The second novelty of the paper is formulation in which, unlike...
Computer vision is a growing field of computer science that intends to extract some useful information from images, usually taken from cameras or scanners. The ability to recognize shapes in images is often necessary in computer vision programs. This article describes how to make a program able to recognize basic geometrical figures by using machine learning. This article shows the image processing...
In this paper, a novel approach that addresses the stereo correspondence problem is proposed. Some recent techniques that transform the stereo correspondence problem to a minimization of a global energy function are based on graph cuts. These techniques based on graph cuts consider all possible disparities between minimum and maximum values for each pixel. The originality of this work is to construct...
In this study, an effective foreground/background segmentation approach for bootstrapping video sequences is proposed. First, a modified block representation approach is used to classify each block of the current video frame into one of the four categories, namely, “background,” “still object,” “illumination change,” and “moving object.” Then, a new background updating scheme is developed, in which...
In this paper, we present a semi-automated method for converting conventional 2D images to stereoscopic 3D. User-defined strokes that correspond to a rough estimate of the depth values in the scene are defined for the image of interest. With these strokes, our system thus determines what the depth values are for the rest of the image, producing a depth map that is ultimately used to create a stereoscopic...
Detection and removal of rain in image is a difficult and crucial problem due to the complexity of rain and its negative effects on image. The spatio-temporal property and the chromatic property of rain are comprehensively analyzed. Using the two properties, a simple but effective algorithm is proposed to detect and remove the rain of sequential images. Firstly time complexity of k-means is reduced...
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