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Face segmentation is an important processing step in a typically face-based person identification system. This paper presents a modified K-means clustering and fusion approach for face region extraction from colorful images of video sequences. It is based on L*a*b* color space analysis and consists of three processing steps: color number estimation, color region clustering, and face region post processing...
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...
In computer vision-based Intelligent Transportation Systems (ITS), one of the key techniques is to exactly detect the vehicles. The common way for vehicle detection is the background difference method. In this paper, we introduce several background extraction and updating methods and develop a new background extraction and update method based on histogram in YCbCr color space. By using YCbCr color...
We present a new method for fully automated video matting. This method uses depth information acquired by a depth camera to automatically compute trimaps. Trimaps segment an image into three nonoverlapping regions (foreground, background, and unknown) and generation of a highly accurate trimap is one of the most important tasks in natural alpha matting. We propose an adaptive approach to generate...
In this work, a novel occlusion detection algorithm using online learning is proposed for video applications. Each frame of a video is considered as a time-step for which pixels are classified as being either occluded or non-occluded. The Hedge algorithm is employed to determine weights for a set of experts, each of which is tuned to detect a specific type of occlusion boundary. In contrast to previous...
Global motion estimation is an important task for various video processing techniques. The estimation itself has to be robust in presence of arbitrarily moving foreground objects. For that task, two different kinds of estimation methods exist. On the one hand, pixel-based approaches deliver more precise results and work more robust on video sequences with foreground objects. On the other hand, when...
Search patterns and the center-biased characteristics of motion vector distribution have large impact on both searching speed and quality of block motion estimation. In this paper, we propose a new cross-hexagon search algorithm (NCHEXS) using two cross-shaped search patterns as the first two initial steps and large/small hexagon-shaped patterns as the subsequent steps for fast block motion estimation...
We present a novel stereo video disparity estimation method. The proposed method is a two-stage algorithm. During the first stage, initial disparity maps are computed in a frame-by-frame basis. In the second stage, the initial estimates are treated as a space-time volume. By setting up an l1-normed minimization problem with a novel three-dimensional total variation regularization, spatial smoothness...
This paper presents a fast algorithm for restoring video sequences. The proposed algorithm, as opposed to existing methods, does not consider video restoration as a sequence of image restoration problems. Rather, it treats a video sequence as a space-time volume and poses a space-time total variation regularization to enhance the smoothness of the solution. The optimization problem is solved by transforming...
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...
Background subtraction is commonly used to detect foreground objects in video surveillance. Traditional background subtraction methods are usually based on the assumption that the background is stationary. However, they are not applicable to dynamic background, whose background images change over time. In this paper, we propose an adaptive Local-Patch Gaussian Mixture Model (LPGMM) as the dynamic...
In order to further improve video coding efficiency, a novel adaptive sub-pixel interpolation filter is presented in this paper. Considering the local image characteristics, the proposed method designs interpolation filters for sub-pixels in low-frequent and high-frequent areas separately. And in order to reduce the header information, flexible symmetry is assumed for each filter. Experimental results...
Images are usually consists of motion translation from one frame to another frame. Motion translation is represented by the pixels value changes based on the pixel density. The motion transition process from one frame to another frame is called motion estimation. Motion estimation is a process to determine the motion vector which represents the motion translation in the successive frames. There are...
In this paper, recognizing human actions has been investigated from video sequences. With morphological gradient and pooling operation, invariant shape of each human body in an action sequence is obtained. Edge feature of invariant shape is extracted to represent human actions. Pyramid Histograms of Orientation Gradients (PHOG) of all invariant shapes in video are averaged to form a feature vector...
In recent years, there has been increased interest in characterizing and extracting 3D information from video sequences for object tracking and identification. In this paper, we propose a single view-based framework for robust estimation of height and position. In this work, 2D features of a target object is back-projected into the 3D scene space where its coordinate system is given by a rectangular...
This paper presents a new method of video sequence segmentation. The principal aim of our approach is the detection of cuts suites in a video sequence (boundaries of transactions). The method is based on two thresholds which allow the localization of transactions suites in a video sequence.
Object tracking is a paramount task in video surveillance systems. Although many efforts have been accomplished on object tracking during the last years more work is still needed in order to generate more robust systems. A new fuzzy method for object tracking is presented in this paper. The proposed method is composed of two Sugeno type systems with weighted average memory output functions. One of...
We present a new graph-based transform for video signals using wavelet lifting. Graphs are created to capture spatial and temporal correlations in video sequences. Our new transforms allow spatial and temporal correlation to be jointly exploited, in contrast to existing techniques, such as motion compensated temporal filtering, which can be seen as "separable" transforms, since spatial and...
We introduce a fast and robust subspace-based approach to appearance-based object tracking. The core of our approach is based on Fast Robust Correlation (FRC), a recently proposed technique for the robust estimation of large translational displacements. We show how the basic principles of FRC can be naturally extended to formulate a robust version of Principal Component Analysis (PCA) which can be...
Digital video contents now become easily available through Internet and various medium. Easy availability made digital video more popular than analog media. And it attains a sharp attention regarding its ownership. The ownership integrity can be easily violated using different video editing software. In this regard we are proposing a chip level framework in accordance with our already proposed LSB...
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