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Dynamosaics: video mosaics with non-chronological time

Dynamosaics: video mosaics with non-chronological time

引用

conference on computer vision and pattern recognition (cvpr)

作者： A. Rav-Acha Y. Pritch D. Lischinski S. Peleg School of Computer Science and Engineering Hebrew University of Jerusalem Jerusalem Israel

With the limited field of view of human vision, our perception of most scenes is built over time while our eyes are scanning the scene. In the case of static scenes, this process can be modeled by panoramic mosaicing: stitching together images into a panoramic view. Can a dynamic scene, scanned by a video camera, be represented with a dynamic panoramic video even though different regions were visible at different times? In this paper, we explore time flow manipulation in video, such as the creation of new videos in which events that occurred at different times are displayed simultaneously. More general changes in the time flow are also possible, which enable re-scheduling the order of dynamic events in the video, for example. We generate dynamic mosaics by sweeping the aligned space-time volume of the input video by a time front surface and generating a sequence of time slices in the process. Various sweeping strategies and different time front evolutions manipulate the time flow in the video, enabling many unexplored and powerful effects, such as panoramic movies.

关键词： Layout Motion pictures Cameras Videoconference Humans Eyes computer science Contracts Stacking Strips

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Online learning of probabilistic appearance manifolds for video-based recognition and tracking

Online learning of probabilistic appearance manifolds for vi...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Kuang-Chih Lee D. Kriegman Urbana-Champaign University of Illinois Urbana-Champaign IL USA Computer Science & Engineering University of California San Diego La Jolla CA USA

This paper presents an online learning algorithm to construct from video sequences an image-based representation that is useful for recognition and tracking. For a class of objects (e.g., human faces), a generic representation of the appearances of the class is learned off-line. From video of an instance of this class (e.g., a particular person), an appearance model is incrementally learned on-line using the prior generic model and successive frames from the video. More specifically, both the generic and individual appearances are represented as an appearance manifold that is approximated by a collection of sub-manifolds (named pose manifolds) and the connectivity between them. In turn, each sub-manifold is approximated by a low-dimensional linear sub-space while the connectivity is modeled by transition probabilities between pairs of sub-manifolds. We demonstrate that our online learning algorithm constructs an effective representation for face tracking, and its use in video-based face recognition compares favorably to the representation constructed with a batch technique.

关键词： Video sequences Principal component analysis Image recognition computer science Machine learning Machine learning algorithms Face recognition Streaming media Manifolds Humans

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Actions sketch: a novel action representation

Actions sketch: a novel action representation

引用

conference on computer vision and pattern recognition (cvpr)

作者： Alper Yilmaz Mubarak Shah School of Computer Science University of Central Florida Orlando FL USA

In this paper, we propose to model an action based on both the shape and the motion of the performing object. When the object performs an action in 3D, the points on the outer boundary of the object are projected as 2D (x, y) contour in the image plane. A sequence of such 2D contours with respect to time generates a spatiotemporal volume (STV) in (x, y, t), which can be treated as 3D object in the (x, y, t) space. We analyze STV by using the differential geometric surface properties to identify action descriptors capturing both spatial and temporal properties. A set of action descriptors is called an action sketch. The first step in our approach is to generate STV by solving the point correspondence problem between consecutive frames. The correspondences are determined using a two-step graph theoretical approach. After the STV is generated, actions descriptors are computed by analyzing the differential geometric properties of STV. Finally, using these descriptors, we perform action recognition, which is also formulated as graph theoretical problem. Several experimental results are presented to demonstrate our approach.

关键词： Shape Legged locomotion Spatiotemporal phenomena Humans computer vision Hidden Markov models Data mining Trajectory computer science Surface treatment

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Formulating semantic image annotation as a supervised learning problem

Formulating semantic image annotation as a supervised learni...

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Carneiro N. Vasconcelos Department of Electrical and Computer Engineering University of California San Diego CA USA Department of Computer Science University of British Columbia Vancouver BC Canada

We introduce a new method to automatically annotate and retrieve images using a vocabulary of image semantics. The novel contributions include a discriminant formulation of the problem, a multiple instance learning solution that enables the estimation of concept probability distributions without prior image segmentation, and a hierarchical description of the density of each image class that enables very efficient training. Compared to current methods of image annotation and retrieval, the one now proposed has significantly smaller time complexity and better recognition performance. Specifically, its recognition complexity is O(C/spl times/R), where C is the number of classes (or image annotations) and R is the number of image regions, while the best results in the literature have complexity O(T/spl times/R), where T is the number of training images. Since the number of classes grows substantially slower than that of training images, the proposed method scales better during training, and processes test images faster This is illustrated through comparisons in terms of complexity, time, and recognition performance with current state-of-the-art methods.

关键词： Supervised learning Image retrieval Image databases Information retrieval Image recognition Visual databases Image segmentation Labeling Unsupervised learning Spatial databases

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Robust L/sub 1/ norm factorization in the presence of outliers and missing data by alternative convex programming

Robust L/sub 1/ norm factorization in the presence of outlie...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Qifa Ke T. Kanade Computer Science Department Carnegie Mellon University Pittsburgh PA USA

Matrix factorization has many applications in computer vision. Singular value decomposition (SVD) is the standard algorithm for factorization. When there are outliers and missing data, which often happen in real measurements, SVD is no longer applicable. For robustness iteratively re-weighted least squares (IRLS) is often used for factorization by assigning a weight to each element in the measurements. Because it uses L/sub 2/ norm, good initialization in IRLS is critical for success, but is nontrivial. In this paper, we formulate matrix factorization as a L/sub 1/ norm minimization problem that is solved efficiently by alternative convex programming. Our formulation 1) is robust without requiring initial weighting, 2) handles missing data straightforwardly, and 3) provides a framework in which constraints and prior knowledge (if available) can be conveniently incorporated. In the experiments we apply our approach to factorization-based structure from motion. It is shown that our approach achieves better results than other approaches (including IRLS) on both synthetic and real data.

关键词： Robustness Cost function Matrix decomposition Application software computer vision Singular value decomposition Noise measurement Maximum likelihood estimation Least squares approximation computer science

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An Illuminance-Reflectance Model for Nonlinear Enhancement of Color Images

An Illuminance-Reflectance Model for Nonlinear Enhancement o...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Li Tao R. Tompkins V.K. Asari Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

An image enhancement algorithm based on illuminance-reflectance model is proposed for improving the visual quality of digital images captured under insufficient and/or non-uniform lighting conditions. The paper presents computational methods for estimation of scene illuminance and reflectance, adaptive dynamic range compression of illuminance, and adaptive enhancement for mid-tone frequency components. The images are processed in a similar way as human eyes sensing a scene. The algorithm demonstrates high quality of enhanced images, robust performance and fast processing speed. Compared with Retinex and multi-scale retinex with color restoration (MSRCR), the proposed method shows a better balance between luminance enhancement and contrast enhancement as well as a more consistent and reliable color rendition without introducing incorrect colors. This is an effective technique for image enhancement with simple computational procedures, which makes real-time application successfully realized. The application of this image enhancement technique to the FRGC images yields improved face recognition results.

关键词： Color Image enhancement Frequency estimation Layout Digital images Reflectivity Dynamic range Image coding Humans Eyes

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Learning a multi-size patch-based hybrid kernel machine ensemble for abnormal region detection in colonoscopic images

Learning a multi-size patch-based hybrid kernel machine ense...

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conference on computer vision and pattern recognition (cvpr)

作者： P. Li K.L. Chan S.M. Krishnan Biomedical Engineering Research Center Nanyang Technological University Singapore

When detecting abnormalities in colonoscopic images, the location, shape and size of the abnormal regions in the image are unknown and vary across images. It is difficult to determine the appropriate patch-size for patch-based approach. So multi-size patches are used simultaneously to represent the image regions and an ensemble is constructed in which each classifier handles one patch size. The combination of classifiers trained using multiple-size patches can recognize abnormal regions more effectively than only using single-size patches. The classification of the image patches can be performed using a discriminative binary support vector machine (SVM) or a recognition-based one-class SVM. Integration of the two types of SVMs is expected to further improve abnormal region detection. Experimental results show the good performance of our proposed ensemble.

关键词： Machine learning Kernel Image segmentation Neoplasms Shape Colonic polyps Support vector machines Support vector machine classification Pixel Image recognition

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Computational Anatomy for Generating 3D Avatars and Boosting Face recognition Systems

Computational Anatomy for Generating 3D Avatars and Boosting...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： M. Vaillant G. Zang J. Aliperti N. Santhanam S. Doucette B. Hoffman M.I. Miller Animetrics Inc. Jackson NH USA

In this paper we present results of an automated system for generating 3D avatars from one or more photographs. We are motivated by the need to support pose and lighting correction for invariant facial identification. Our approach is to extend techniques from the now well established Computational Anatomy field to accommodate the projective geometry associated with video imagery. We present the general Compuational Anatomy framework, describe its merger with and application to the projective geometry setting, and present validation results on FRGC EXP 1.0.1, FRGC EXP 1.0.4, and FERET databases. In particular, we find sub-degree bias in rigid motion accuracy for avatar generation, and 1/20 eye distance average errors in feature landmark accuracy.

关键词： Anatomy Avatars Boosting Face recognition Face detection Robustness Photometry Computational geometry Image databases Spatial databases

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Pixel-Aligned Warping for Multiprojector Tiled Displays

Pixel-Aligned Warping for Multiprojector Tiled Displays

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： M. Hereld R.L. Stevens Computation Institute University of Chicago and Argonne National Laboratory USA Department of Computer Science University of Chicago USA

Multiprojector tiled displays offer a scalable path to high-resolution display systems, often in a large format. Such displays have been employed in a range of applications from scientific visualization to collaborative virtual environments. Images projected onto these systems have always looked less sharp than expected owing to the image warping required to achieve geometrical alignment of the partial images to form the seamless whole. Similar degradation of image quality accompanies keystone correction techniques and image warping onto nonplanar surfaces used in single projector applications. In this paper we discuss the underlying cause of the degradation of apparent image resolution, and we introduce a new class of warping techniques, called pixel-aligned warping, that tend to preserve image sharpness at the expense of strict adherence to underlying geometrical constraints that define the desired warp. We demonstrate how such techniques can be used to significantly improve the apparent sharpness of the final image.

关键词： computer displays Pixel Degradation Rendering (computer graphics) Frequency computer science Laboratories Application software Image resolution Image reconstruction

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Segmentation of a piece-wise planar scene from perspective images

Segmentation of a piece-wise planar scene from perspective i...

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conference on computer vision and pattern recognition (cvpr)

作者： A.L. Yang S. Rao A. Wagner Yi Ma Coordinated Science Laboratory University of Illinois Urbana-Champaign IL USA

We study and compare two novel embedding methods for segmenting feature points of piece-wise planar structures from two (uncalibrated) perspective images. We show that a set of different homographies can be embedded in different ways to a higher-dimensional real or complex space, so that each homography corresponds to either a complex bilinear form or a real quadratic form. Each embedding reveals different algebraic properties and relations of homographies. We give a closed-form segmentation solution for each case by utilizing these properties based on subspace-segmentation methods. These theoretical results show that one can intrinsically segment a piece-wise planar scene from 2-D images without explicitly performing any 3-D reconstruction. The resulting segmentation may make subsequent 3-D reconstruction much better-conditioned. We demonstrate the proposed methods with some convincing experimental results.

关键词： Image segmentation Layout Three dimensional displays Transmission line matrix methods Image reconstruction Image sequences computer vision Tracking Geometry Cameras

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