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.
An image retrieval system is a technique for browsing, searching and retrieving images from a big database of digital images. In this paper, we propose a new content-based image retrieval system that can solve the object and scene recognition problems and categorize similar images. The proposed model consists of a deep structure support vector machine with Gaussian mixture model, which is combined...
In the process of human computer interaction, hand tracking is of great importance. A practical hand tracking method based on improved particle filters with elliptical region covariance descriptors is proposed. Firstly, an elliptical tracking window containing the hand is determined manually in the initial frame. Based on the HSV color model, the color feature of bare hands is extracted, and color...
Vehicle identification is one of the frequently studied problems in video surveillance. Commonly, identifying an unknown vehicle object requires a large amount of training instances. Unfortunately, in the large parking scenario, the cost may be prohibitively expensive because of the finitely waiting time from the car owners. In this paper, we show that it is possible to identify a registered vehicle...
The traditional methods of detecting oil depots usually use Hough transform and template matching, which often have lower detection rates and are difficult to implement. An efficient two-step detection framework is proposed in this paper to detect oil depots in high resolution remote sensing images. In the first stage, LC saliency model is used to detect the salient regions and shows a good performance...
In this paper, we analyze the BER performance of our proposed GCM method under the channel model provided by the IEEE 802.15.7r1 and compare the performance with the intensity based modulations. Through simulations, it will be shown that GCM based performance is generally superior to that of intensity based PAM in most indoor positions. GCM will be applied in wide range of VLC applications as an alternative...
As technology developed, the surveillance system has been widely used in our daily lives. Monitoring systems, background filtering is a very important technology. Even so, in that respect are different dynamics in the surrounding ground for background filtering is a challenging problem, for example: leaves of the shaking, water fluctuations, the display flashes, the light changes to easily filter...
The goal of salient object detection is to estimate the regions which are most likely to attract human's visual attention. As an important image preprocessing procedure to reduce the computational complexity, salient object detection is still a challenging problem in computer vision. In this paper, we proposed a salient object detection model by integrating local and global superpixel contrast at...
Recently, the local stereo matching algorithms based on the adaptive weighting achieve very accurate disparity maps. Compared to global matching approaches, the local algorithms offer less complexities. However, these methods are still beyond hardware ability for real-time application. In this paper, a novel linear stereo matching algorithm with constant execution time is proposed. To begin with,...
Labeling salient region accurately in video with cluttered background and complex motion condition is still a challenging work. In this paper, an efficient and low complexity spatiotemporal consistency optimization model, and a video saliency framework using the spatiotemporal consistency are proposed. We derive the superpixel-level spatial and temporal saliency value by integrating three spatial...
This paper proposes a novel model, called Similarity Based on Visual Attention Features (SimVisual), to enhance the similarity analysis between images by considering features extracted from salient regions mapped by visual attention models. Visual attention models have demonstrated to be very useful for encoding perceptual semantic information of the image content. Thus, aggregating saliency features...
The modeling of visual attention has gained much interest during the last few years since it allows to efficiently drive complex visual processes to particular areas of images or video frames. Although the literature concerning bottom-up saliency models is vast, we still lack of generic approaches modeling top-down task and context-driven visual attention. Indeed, many top-down models simply modulate...
Imaging of renal artery stenosis (RAS) has great clinical importance to reduce the risk of renal disorders. The hemodynamical information is crucial for stenosis detection. In this study, realistic computational models of RAS have been designed to investigate hemodisturbances and collect spatio-temporal locations of blood particles for simulating and validating ultrasound color flow images of RAS...
Detection of the most interesting region in an image has become an important subject in computer vision. Bottom-up model detects regions that differ with respect to their surrounding ones. These regions are known as salient regions. In this paper, we propose a new bottom-up model for saliency detection using the color of background regions. In the model, first, the image is segmented into superpixels...
This paper proposes a system-on-chip (SoC) FPGA — based real-time video processing platform for background and foreground identification. Background and foreground identification is a co mmon feature in many tasks in video content analytics (VCA), including object detection, tracking, segmentation and recognition. VCA is a relatively new field in video processing; it has generally been implemented...
Video-based object recognition faces the problem of multi-view object variance, noisy conditions, and limited computational resources. In our previous work, we introduced a multi-view recognition approach with a compact global image descriptor coupled with orientation sensor data. Since our purpose is to run all computations in a handheld device, contrary to more intensive deep learning approaches,...
Nowadays, high dynamic range imaging techniques are often applied for outdoor applications that may encounter scenes with an extremely high dynamic range. In such scenes, a halo can be produced by gradient reversal, and color information is easily damaged. In this paper, we propose an exposure fusion algorithm that does not suffer from any artifacts in extremely high dynamic range scenes. Using the...
This paper propose an adaptable block-based background modeling and real time image object detection algorithm. In training step, we present adaptable block-based background model that uses major color number to determine the block size. This background model can reduce the memory consumption, efficiently. In detection step, we use one pixel to compare with background model. Then, it can reduce processing...
The identification and secret-key generation system is modelled with Colored Petri Net, that are the modern extension of Classical Petri Net. The major goal of modelling Identification and Secret-key Generation System with Colored Petri Net is to reveal the existence of mistakes and accidents in the model, the behaviour of functioning of the model, the efficiency of the model. The graph of Colored...
In this paper, a framework of generating dynamic fireworks with a steady scene as the background is proposed. We use the particle system for simulating the firework animation to obtain a video clip, which can then be modified based on physical dynamics and the dissemination of light source. To achieve this goal, the general-purpose computation on graphics processing unit (GPGPU) for rendering and...
This paper addresses two graphical processing approaches for computation of edge scattering with Physical Theory of Diffraction (PTD) high-frequency approximation. One is based on processing only a bitmap containing an image of the radar target, while the other uses a bitmap graphical processing algorithm to identify illuminated and shadowed facet mesh vertices, published in 2014, and then computes...
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.