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EXPRESSION MORPHING BETWEEN DIFFERENT ORIENTATIONS
Title
EXPRESSION MORPHING BETWEEN DIFFERENT ORIENTATIONS.
Creator
Fu, Tao, Foroosh, Hassan R., University of Central Florida
Abstract / Description
How to generate new views based on given reference images has been an important and interesting topic in the area of image-based rendering. Two important algorithms that can be used are field morphing and view morphing. Field morphing, which is an algorithm of image morphing, generates new views based on two reference images which were taken at the same viewpoint. The most successful result of field morphing is morphing from one person's face to the other one's face. View morphing, which is...
Show moreHow to generate new views based on given reference images has been an important and interesting topic in the area of image-based rendering. Two important algorithms that can be used are field morphing and view morphing. Field morphing, which is an algorithm of image morphing, generates new views based on two reference images which were taken at the same viewpoint. The most successful result of field morphing is morphing from one person's face to the other one's face. View morphing, which is an algorithm of view synthesis, generates in-between views based on two reference views which were taken at different viewpoints for the same object. The result of view morphing is often an animation of moving one object from the viewpoint of one reference image to the viewpoint of the other one.In this thesis, we proposed a new framework that integrates field morphing and view morphing to solve the problem of expression morphing. Based on four reference images, we successfully generate the morphing from one viewpoint with one expression to another viewpoint with a different expression. We also proposed a new approach to eliminate artifacts that frequently occur in view morphing due to occlusions and in field morphing due to some unforeseen combination of feature lines. We solve these problems by relaxing the monotonicity assumption to piece-wise monotonicity along the epipolar lines. Our experimental results demonstrate the efficiency of this approach in handling occlusions for more realistic synthesis of novel views.
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Date Issued
2004
Identifier
CFE0000070, ucf:46110
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000070
A STATISTICAL APPROACH TO VIEW SYNTHESIS
Title
A STATISTICAL APPROACH TO VIEW SYNTHESIS.
Creator
Berkowitz, Phillip, Shah, Mubarak, University of Central Florida
Abstract / Description
View Synthesis is the challenging problem of predicting a new view or pose of an object given an exemplar view or set of views. This thesis presents a novel approach for the problem of view synthesis. The proposed method uses global features rather than local geometry to achieve an effect similar to that of the well known view morphing method . While previous approaches to the view synthesis problem have shown impressive results, they are highly dependent on being able to solve for epipolar...
Show moreView Synthesis is the challenging problem of predicting a new view or pose of an object given an exemplar view or set of views. This thesis presents a novel approach for the problem of view synthesis. The proposed method uses global features rather than local geometry to achieve an effect similar to that of the well known view morphing method . While previous approaches to the view synthesis problem have shown impressive results, they are highly dependent on being able to solve for epipolar geometry and therefore have a very precise correspondence between reference images. In cases where this is not possible such as noisy data, low contrast data, or long wave infrared data an alternative approach is desirable. Here two problems will be considered. The proposed view synthesis method will be used to synthesis new views given a set of reference views. Additionally the algorithm will be extended to synthesis new lighting conditions and thermal signatures. Finally the algorithm will be applied toward enhancing the ATR problem by creating additional training data to increase the likelihood of detection and classification.
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Date Issued
2009
Identifier
CFE0002684, ucf:48214
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002684
IMAGE BASED VIEW SYNTHESIS
Title
IMAGE BASED VIEW SYNTHESIS.
Creator
Xiao, Jiangjian, Shah, Mubarak, University of Central Florida
Abstract / Description
This dissertation deals with the image-based approach to synthesize a virtual scene using sparse images or a video sequence without the use of 3D models. In our scenario, a real dynamic or static scene is captured by a set of un-calibrated images from different viewpoints. After automatically recovering the geometric transformations between these images, a series of photo-realistic virtual views can be rendered and a virtual environment covered by these several static cameras can be...
Show moreThis dissertation deals with the image-based approach to synthesize a virtual scene using sparse images or a video sequence without the use of 3D models. In our scenario, a real dynamic or static scene is captured by a set of un-calibrated images from different viewpoints. After automatically recovering the geometric transformations between these images, a series of photo-realistic virtual views can be rendered and a virtual environment covered by these several static cameras can be synthesized. This image-based approach has applications in object recognition, object transfer, video synthesis and video compression. In this dissertation, I have contributed to several sub-problems related to image based view synthesis. Before image-based view synthesis can be performed, images need to be segmented into individual objects. Assuming that a scene can approximately be described by multiple planar regions, I have developed a robust and novel approach to automatically extract a set of affine or projective transformations induced by these regions, correctly detect the occlusion pixels over multiple consecutive frames, and accurately segment the scene into several motion layers. First, a number of seed regions using correspondences in two frames are determined, and the seed regions are expanded and outliers are rejected employing the graph cuts method integrated with level set representation. Next, these initial regions are merged into several initial layers according to the motion similarity. Third, the occlusion order constraints on multiple frames are explored, which guarantee that the occlusion area increases with the temporal order in a short period and effectively maintains segmentation consistency over multiple consecutive frames. Then the correct layer segmentation is obtained by using a graph cuts algorithm, and the occlusions between the overlapping layers are explicitly determined. Several experimental results are demonstrated to show that our approach is effective and robust. Recovering the geometrical transformations among images of a scene is a prerequisite step for image-based view synthesis. I have developed a wide baseline matching algorithm to identify the correspondences between two un-calibrated images, and to further determine the geometric relationship between images, such as epipolar geometry or projective transformation. In our approach, a set of salient features, edge-corners, are detected to provide robust and consistent matching primitives. Then, based on the Singular Value Decomposition (SVD) of an affine matrix, we effectively quantize the search space into two independent subspaces for rotation angle and scaling factor, and then we use a two-stage affine matching algorithm to obtain robust matches between these two frames. The experimental results on a number of wide baseline images strongly demonstrate that our matching method outperforms the state-of-art algorithms even under the significant camera motion, illumination variation, occlusion, and self-similarity. Given the wide baseline matches among images I have developed a novel method for Dynamic view morphing. Dynamic view morphing deals with the scenes containing moving objects in presence of camera motion. The objects can be rigid or non-rigid, each of them can move in any orientation or direction. The proposed method can generate a series of continuous and physically accurate intermediate views from only two reference images without any knowledge about 3D. The procedure consists of three steps: segmentation, morphing and post-warping. Given a boundary connection constraint, the source and target scenes are segmented into several layers for morphing. Based on the decomposition of affine transformation between corresponding points, we uniquely determine a physically correct path for post-warping by the least distortion method. I have successfully generalized the dynamic scene synthesis problem from the simple scene with only rotation to the dynamic scene containing non-rigid objects. My method can handle dynamic rigid or non-rigid objects, including complicated objects such as humans. Finally, I have also developed a novel algorithm for tri-view morphing. This is an efficient image-based method to navigate a scene based on only three wide-baseline un-calibrated images without the explicit use of a 3D model. After automatically recovering corresponding points between each pair of images using our wide baseline matching method, an accurate trifocal plane is extracted from the trifocal tensor implied in these three images. Next, employing a trinocular-stereo algorithm and barycentric blending technique, we generate an arbitrary novel view to navigate the scene in a 2D space. Furthermore, after self-calibration of the cameras, a 3D model can also be correctly augmented into this virtual environment synthesized by the tri-view morphing algorithm. We have applied our view morphing framework to several interesting applications: 4D video synthesis, automatic target recognition, multi-view morphing.
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Date Issued
2004
Identifier
CFE0000218, ucf:46276
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000218