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Background subtraction is a technique for detecting moving objects in video frames. A simple BS process involves building a model of the background and extracting regions of the foreground (moving objects) with the assumptions that the camera remains stationary and there exist no movements in the background. Video object extraction is a critical task in multimedia analysis and editing. Normally, the...
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...
Conventional stereoscopic video content production requires use of dedicated stereo camera rigs which is both costly and lacking video editing flexibility. In this paper, we propose a novel approach which only requires a small number of standard cameras sparsely located around a scene to automatically convert the monocular inputs into stereoscopic streams. The approach combines a probabilistic spatio-temporal...
This paper deals with tracking of object with assistance by interactive deformation contour using Graph cut method. The method is used for the segmentation of tracked object on individual video frames. At the beginning of this method, user interactively defines object destined for tracking by defining its contour. The initialization of Graph cut method by determining of terminals of the object and...
Video endoscopy is one of the standard clinical procedures for visually detecting lesions on the internal wall of human bladders. In order to facilitate the diagnosis, it is helpful to build panoramic maps by registering consecutive images from the video sequence. We show how to efficiently reduce the computation time of graph cut based image registration by an order of magnitude. The number of nodes...
Video retargeting is the task of fitting standard-sized video into arbitrary screen. A compelling retargeting attempts to preserve most visual information of original video as well as deliver a temporally consistent retargeted view. To handle long video sequences, we perform the task on a shot/subshot basis. For each frame, a crop pane is determined to optimally select a region of interest as the...
GMM based algorithms have become the de facto standard for background subtraction in video sequences, mainly because of their ability to track multiple background distributions, which allows them to handle complex scenes including moving trees, flags moving in the wind etc. However, it is not always easy to determine which distributions of the mixture belong to the background and which distributions...
In this paper, a quasi-automatic video matting approach which can preserve the temporal consistency of the alpha mattes is presented. “Quasi-automatic” means that it only needs a few user interactions on the first frame. A new algorithm which incorporates the Bayesian Estimation, Weighted Kernel Density Estimation (WKDE) and graph cut is presented to automatically and accurately segment each frame...
We study the problem of event detection from realistic videos with repetitive sequential human activities. Despite the large body of work on event detection and recognition, very few have addressed low-quality videos captured from realistic environments. Our framework is based on solving the shortest path on a temporal-event graph constructed from the video content. Graph vertices correspond to detected...
In this paper we present a segmentation system for monocular video sequences with static camera that aims at foreground/background separation and tracking. We propose to combine a simple pixel-wise model for the background with a general purpose region based model for the foreground. The background is modeled using one Gaussian per pixel, thus achieving a precise and easy to update model. The foreground...
We present an inpainting method for images and videos based on nonlocal discrete p-Laplace regularization on weighted graphs. Our work has the advantage of unifying local geometric methods and nonlocal exemplar-based ones in the same framework. Our image inpainting benefits from local and nonlocal regularities within the image. In addition to that, our video inpainting exploits temporal and spatial...
This paper addresses gradual transition detection which is part of video segmentation problem, and consists in identifying the boundary between consecutive shots. In this work, we propose an approach to cope with gradual transition detection in which we define and use a new dissimilarity measure based on the size of the maximum cardinality matching calculated using a bipartite graph with respect to...
We present a video shot boundary detection algorithm based on the novel graph theoretic concept, namely dominant sets. Dominant sets are defined as a set of the nodes in a graph, mostly similar to each other and dissimilar to the others. In order to achieve this goal, candidate shot boundaries are determined by using simply pixel-wise differences between consequent frames. For each candidate position,...
This paper proposes a new method for achieving precise video segmentation without any supervision or interaction. The main contributions of this report include 1) the introduction of fully automatic segmentation based on the maximum a posteriori (MAP) estimation of the Markov random field (MRF) with graph cuts and saliency-driven priors and 2) the updating of priors and feature likelihoods by integrating...
In this paper, a novel texture synthesis approach with spatio-temporal boundary conditions is presented. The proposed method is non-parametric and patch-based. Blending between overlapping patches is optimized using a graph-cut technique. Furthermore, a set of photometric correction algorithms, namely Poisson [1] and covariant [2] cloning, is used simultaneously to fit continuation patches into a...
Cut detection is part of the video segmentation problem, and consists in the identification of the boundary between consecutive shots. In this case, when two consecutive frames are similar, they are considered to be in the same shot. This work presents an approach to cut detection using a rotation and translation invariant algorithm based on the use of the maximum cardinality of a bipartite graph...
We address the problem of video super resolution - obtaining a single high-resolution video whose spatial and temporal resolutions are higher than any of the input low-resolution videos. We employ a reconstruction based approach using MRF -MAP formalism, and use approximate optimization using graph cuts to carry out the reconstruction. We show that in our formulation it is possible to selectively...
We propose a new solution to the problem of bi-layer video segmentation in terms of both, hardware design and algorithmic solution. At the data acquisition stage, we combine color video with infrared video, which is robust to illumination changes and provides an automatic initialization of the cue map for foreground-background segmentation. Two algorithms are presented to complete the segmentation,...
The video segmentation problem consists in the identification of the boundary between consecutive shots. When two consecutive frames are similar, they are considered to be in the same shot. In this work, we use the maximum cardinality of the bipartite graph matching between two frames as the dissimilarity distance in order to identify the cut locations. Thus, if two frames are similar then the maximum...
This paper proposes an automatic foreground segmentation system based on Gaussian mixture models and dynamic graph cut algorithm. An adaptive per-pixel background model is developed to set the data cost of an image graph. Shadow detection which is important to the foreground segmentation is introduced in this paper. A boundary smoothing algorithm is presented so as to eliminate edge aliasing and composite...
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