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.
We present a method for foreground-background video segmentation in real-time that may be used in applications as, for instance, Background Substitution, Analysis of Surveillance Cameras, Highway Cars Detection and so on. Our approach implements a probabilistic segmentation based on the binary Quadratic Markov Measure Fields models (QMMFs). That framework regularizes the likelihood of each pixel to...
In this paper we propose multiple cameras using real time tracking for surveillance and security system. It is extensively used in the research field of computer vision applications, like that video surveillance, authentication systems, robotics, pre-stage of MPEG4 image compression and user inter faces by gestures. The key components of tracking for surveillance system are extracting the feature,...
This paper presents a method to estimate alpha mattes for video sequences of the same foreground scene from wide-baseline views given sparse key-frame trimaps in a single view. A statistical inference framework is introduced for spatio-temporal propagation of high-confidence trimap labels between video sequences without a requirement for correspondence or camera calibration and motion estimation....
In this paper we introduce an unsupervised scheme for the segmentation of motion layers in video sequences. The number of layers is automatically determined by the method. Our approach first extracts the motion models thanks to a RANSAC-based random sampling algorithm improved by the use of geodesic distance information. Then those models are assigned to pixels in the color image by minimizing an...
Exposure Fusion and other HDR techniques generate well-exposed images from a bracketed image sequence while reproducing a large dynamic range that far exceeds the dynamic range of a single exposure. Common to all these techniques is the problem that the smallest movements in the captured images generate artefacts (ghosting) that dramatically affect the quality of the final images. This limits the...
Acquisition of consistent multi-camera image data such as for time-slice sequences (widely known by their use as cinematic effects, e.g. in “The Matrix”) is a challenging task, especially when using low-cost image sensors. Many different steps such as camera calibration and color conformation are involved, each of which poses individual problems. We have developed a complete and extendable setup for...
We present an algorithm for estimating dense image correspondences. Our versatile approach lends itself to various tasks typical for video post-processing, including image morphing, optical flow estimation, stereo rectification, disparity/depth reconstruction and baseline adjustment. We incorporate recent advances in feature matching, energy minimization, stereo vision and data clustering into our...
Optical flow methods, such as Lucas-Kanade and Horn-Schunck algorithms, are popular in motion estimation. However, they fall short on accuracy when they are applied to blurred videos. Some people utilize hybrid camera system to get a low resolution image to suppress the blurring effect so that more accurate optical flow for blurred high resolution image can be further derived, though in most of the...
The fusion of images captured from Electrical-Optical (EO) and Infra-Red (IR) cameras has been extensively studied for military applications in recent years. In this paper, we propose a novel wavelet-based framework for online fusion of EO and IR image sequences. The proposed framework provides multiple fusion rules for image fusion as well as a novel edge-based evaluation method to select the optimal...
This paper deals with automatic characterization of video capture actions like scale change (zoom) or translation (traveling) in a video sequence. The overall objective is to enhance the scripted quality while capturing a video sequence by professionals or non professionals. Ultimately, the capture actions would use a predefined video template, progressively filled by the cameraman and automatically...
Recently, Distributed Video Coding (DVC) has been actively studied as a solution to the growing demands on light video encoder. However, DVC shifts the complexity from the encoder to the decoder side, and in some applications it needs unacceptably long decoding time and/or big computing power. In this paper, we propose a Wyner-Ziv (WZ) video coding which extracts fast moving regions called Region-Of-Interest...
This paper presents a performance evaluation of two different sub-pixel motion estimation algorithms, one base on Block-Matching and the other based on optical flow to obtain sub-pixel displacement. On block-matching, we focus on block-based full search (FS), three step search (TSS), two dimensional logarithm search (TDL), cross search algorithm (CSA), a new three step search algorithm (NTSS), a novel...
Pedestrian detection is one of the most important techniques for surveillance applications. This paper proposes an effective method for pedestrian detection in low-contrast images. The main characteristic of the proposed method is a two-stage moving object extraction. In the first stage, the watershed algorithm is used to extract multiple regions of moving objects. In the second stage, a novel criterion...
We proposed a color video generation method for spatio-temporal high resolution video imaging in dark conditions. The method (dual resolutions and exposures(DRE) method) consists of a high sensitive imaging with employing long time exposure and a subsequent spatio-temporal decomposition process which suppresses a motion blur caused by the long time exposure. Imaging step captures RGB color video sequences...
In this paper, we propose a macro-observation scheme for unusual event detection in daily life, where motions in time-space domain are described by a global representation and individual activities do not have to be defined and modeled beforehand. The proposed representation records the time-space energy of motions of all moving objects in a scene without segmenting individual object parts or tracking...
Super-resolution is a very well-studied topic in image enhancement. However, traditional super-resolution techniques are limited by global motion assumption and the accuracy of displacement estimation. In this paper, we are interested in the problem of constructing super-resolution images from high-speed camera sequences with the presence of moving objects. The objective of our research is finding...
Traffic Signs provide drivers with very valuable information about the road, in order to make driving safer and easier. They are designed to be easily recognized by human drivers mainly because their color and shape are very different from natural environments. Automatic traffic sign detection and recognition is important in the development of unmanned vehicles, and is expected to provide information...
Human face detection is a key technology in face information processing, the speed of which is very important during real-time face detection for input images or input video sequences. This paper presents a novel face window searching algorithm based on evolutionary agent when detecting faces in gray-scale images. It can quickly And the candidate face windows through the evolutionary computation of...
Traffic sign, especially speed limit sign recognition is important in a driver assistance system. In this paper, a robust approach for real-time detection and recognition of speed limit sign is presented. It consists of two major steps: sign detection and sign recognition. In detection stage, Fast Radial Symmetry Transform is utilized to detect possible sign locations. Then the new method proposed,...
Scene change detection is an essential step for archived films restoration. But the image quality of archived films often degrades gradually which makes false detection during shot segmentation. This paper focuses on some problems about the scene change detection in archived films. For abrupt change shot detection, the difference between histograms of block-bases adjacent frames and across frames...
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.