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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...
Three dimensional (3-D) video is experiencing a rapid growth in a number of areas, including 3-D cinema, 3-D TV, and mobile phones. Several problems must be addressed to display captured 3-D video at another location. One problem is how to represent the data. The multiview plus depth representation of a scene requires a lower bit rate than transmitting all views required by an application and provides...
Panoramic-image-based approach for representing environmental data has become a common method used by various virtual reality applications. It has many advantages over the traditional 3D modeling approaches, such as shorter generation times, faster rendering speeds, higher photorealism, and less storage needed. The drawback is however that it stores only static information of the scene. Panoramic...
Vision algorithms face many challenging issues when it comes to analyze human activities in video surveillance applications.For instance, occlusions makes the detection and tracking of people a hard task to perform. Hence advanced and adapted solutions are required to analyze the content of video sequences. We here present a people detection algorithm based on a hierarchical tree of Histogram of Oriented...
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 introduce a unified framework for scene structure and motion estimation on road-driving stereo sequences. This framework is based on the slanted-plane scene model that has become widely popular in the stereo vision community. Our algorithm iteratively and alternately solves for scene structure and motion. Surface estimation is done using our own slanted-plane stereo algorithm. Motion estimation...
Multiple Description Coding has recently proved to be an effective solution for the robust transmission of 3D video sequences over unreliable channels. The paper presents a novel Cognitive Source Coding scheme that improves the performance of traditional MDC schemes by combining adaptively traditional predictive and Wyner-Ziv codings according to the characteristics of the video sequence and to the...
Face recognition from video has been extensively studied in recent years. Intuitively, video provides more information than a single image. But problems such as variation in pose and occlusion still remain. When a face is partially occluded, handling the occluded part of the face is an especially challenging task. In this paper, we propose a novel method to recognize a face from video based on face...
In this work, we present novel algorithm that permits converting 2D video color sequence into 3D one via the region based stereo matching in order to obtain the depth maps from video sequence. These depth maps were applied to design 3D video being observed via an anaglyph in a cheaper way. The anaglyphs were designed by manipulation with red component gathering two neighbor 2D frames of the video...
The key issue addressed by this paper is the necessity to devise performance evaluation measures for systems that integrate multiple cues for tracking in video sequences. We propose a generic evaluation approach that can be implemented in systems that perform higher-level people tracking by integrating multiple low-level features extracted from the video data. Two new measures: video sequence accuracy...
A generalized expectation maximization (GEM) algorithm is used to retrieve the pose of a person from a monocular video sequence shot with a moving camera. After embedding the set of possible poses in a low dimensional space using principal component analysis, the configuration that gives the best match to the input image is held as estimate for the current frame. This match is computed iterating GEM...
In this paper we propose a novel approach to use both motion and disparity information to compress 3D integral video sequences. The integral video sequence is decomposed into 8 viewpoint video sequences and a block search is performed to jointly exploit the motion and disparity redundancies to maximize the compression. A half pixel refinement algorithm is then applied by interpolating macro blocks...
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