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Activity Analysis in Microtubule Videos by Mixture of Hidden Markov Models

Activity Analysis in Microtubule Videos by Mixture of Hidden...

引用

conference on computer vision and pattern recognition (CVPR)

作者： A. Altinok M. El-Saban A.J. Peck L. Wilson S.C. Feinstein B.S. Manjunath K. Rose Computer Science University of California Santa Barbara CA USA Electrical and Computer Engineering University of California Santa Barbara CA USA Molecular Cellular and Developmental Biology University of California Santa Barbara CA USA

We present an automated method for the tracking and dynamics modeling of microtubules -a major component of the cytoskeleton- which provides researchers with a previously unattainable level of data analysis and quantification capabilities. The proposed method improves upon the manual tracking and analysis techniques by i) increasing accuracy and quantified sample size in data collection, ii) eliminating user bias and standardizing analysis, iii) making available new features that are impractical to capture manually, iv) enabling statistical extraction of dynamics patterns from cellular processes, and v) greatly reducing required time for entire studies. An automated procedure is proposed to track each resolvable microtubule, whose aggregate activity is then modeled by mixtures of Hidden Markov Models to uncover dynamics patterns of underlying cellular and experimental conditions. Our results support manually established findings on an actual microtubule dataset and illustrate how automated analysis of spatial and temporal patterns offers previously unattainable insights to cellular processes.

关键词： Videos Hidden Markov models pattern analysis Cells (biology) Biological system modeling computer vision Biology computing Data analysis Data mining Application software

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Space-Time Video Montage

Space-Time Video Montage

引用

conference on computer vision and pattern recognition (CVPR)

作者： Hong-Wen Kang Y. Matsushita Xiaoou Tang Xue-Quan Chen University of Science and Technology Hefei China University of Science and Technology of China Hefei P.R. China Microsoft Research Asia Beijing P.R. China China

Conventional video summarization methods focus predominantly on summarizing videos along the time axis, such as building a movie trailer: The resulting video trailer tends to retain much empty space in the background of the video frames while discarding much informative video content due to size limit. In this paper we propose a novel spacetime video summarization method which we call space-time video montage. The method simultaneously analyzes both the spatial and temporal injbrmation distribution in a video sequence, and extracts the visually informative space-time portions of the input videos. The informative video porlions are represented in volumetric layers. The layers are then packrd together in a smull ouzput video volume such that the total amount of visual information in the video volume is maximized. To achieve the packing process, we develop a new algorithm based upon the first-fit and Graph cut optimization techniques. Since our method is uble to cut off spatially und temporally less informative portions, it is uble to generate much more compact yet highly informative output videos. The effecliveness of our method is validated by extensive experiments over a wide variety of videos.

关键词： Videoconference Video sequences computer vision pattern recognition Space technology Motion pictures Data security Asia Streaming media Data mining

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Belief Propagation Driven Method for Facial Gestures recognition in Presence of Occlusions

Belief Propagation Driven Method for Facial Gestures Recogni...

引用

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

作者： Wei-Kai Liao I. Cohen Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA

In this paper, we present a framework for automatic facial gestures recognition in a highly interactive environment. We propose to use a region-based representation of the face, and model the interdependencies of these regions using a graphical model. A parametric modeling of the local facial deformations and the use of a graphical model facilitate the characterization of intra-region dynamic patterns and the inter-region dependencies. We augment this formalism with a belief propagation algorithm to infer missing data, as well as correcting for erroneous estimations of the local deformations. The resulting approach hence handles complete observation and partial occlusion cases in an unified way, and allows for the recognition of facial gestures in presence of head motion and partial occlusions of the face. Experimental results on recognizing facial expression in various real world situations, such as non-frontal views, moving head, and occlusions illustrate the proposed approach.

关键词： Belief propagation Face recognition Graphical models Face detection Intelligent robots Parametric statistics computer vision Robotics and automation Intelligent systems Emotion recognition

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Segmentation of Neighboring Structures by Modeling Their Interaction

Segmentation of Neighboring Structures by Modeling Their Int...

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

作者： Pingkun Yan Mubarak Shah School of Computer Science University of Central Florida USA

The similarity of pixel intensities, presence of noise, existence of partial volume effect and so on make segmentation of neighboring structures in medical image a challenging task. In this paper, we present a novel approach for segmenting multiple neighboring organs simultaneously by modeling interaction between them. Our method is motivated by the observation that radiologists mark ambiguous boundaries by considering all surrounding anatomic structures. In the proposed interaction model, the connectedness, competition and repulsion between organs are analyzed. By quantitatively defining these interaction components, an energy functional is formulated and structures are obtained by minimizing the energy. An energy minimization algorithm based on multiway graph cuts is proposed, which obtains an approximation within a known factor of the global minimum. The promising experimental results on various medical images demonstrate the performance of our segmentation algorithm.

关键词： Image segmentation Deformable models Biomedical imaging Level set Minimization methods Anatomical structure computer vision Topology computer science Pixel

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Multi-Resolution Patch Tensor for Facial Expression Hallucination

Multi-Resolution Patch Tensor for Facial Expression Hallucin...

引用

conference on computer vision and pattern recognition (CVPR)

作者： Kui Jia Shaogang Gong Department of Computer Science Queen''s Mary University of London UK

In this paper, we propose a sequential approach to hallucinate/ synthesize high-resolution images of multiple facial expressions. We propose an idea of multi-resolution tensor for super-resolution, and decompose facial expression images into small local patches. We build a multi-resolution patch tensor across different facial expressions. By unifying the identity parameters and learning the subspace mappings across different resolutions and expressions, we simplify the facial expression hallucination as a problem of parameter recovery in a patch tensor space. We further add a high-frequency component residue using nonparametric patch learning from high-resolution training data. We integrate the sequential statistical modelling into a Bayesian framework, so that given any low-resolution facial image of a single expression, we are able to synthesize multiple facial expression images in high-resolution. We show promising experimental results from both facial expression database and live video sequences.

关键词： Tensile stress Image resolution Training data Bayesian methods Image databases Video sequences Robustness Active appearance model Cameras Principal component analysis

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A Proposed Pipelined-Architecture for FPGA-Based Affine-Invariant Feature Detectors

A Proposed Pipelined-Architecture for FPGA-Based Affine-Inva...

引用

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

作者： C. Cabani W.J. MacLean Department of Electrical & Computer Engineering University of Toronto Toronto ONT Canada

This paper describes a hardware architecture for an FPGAbased implementation of affine-invariant image feature detectors, following the algorithm of Mikolajczyk & Schmid. The architecture mimics the structure of the algorithm by implementing a multi-scale Harris corner detector which feeds candidate points into an iterative procedure to determine the local affine shape of the feature’s neighbourhood (up to an undetermined rotation). Since the algorithm is iterative, and since we desire a high throughput rate, the iterations are "unrolled" into a sequence of identical computation blocks arranged in a pipeline architecture. The modularity of the resulting architecture allows for scaling the implementation to devices of different resource capacity, as well as partitioning the algorithm over several devices. The final implementation, when completed, will be part of a smart-camera system which outputs features at the same time as the associated images.

关键词： computer vision Iterative algorithms Detectors Partitioning algorithms computer architecture Hardware Feeds Shape Throughput Pipelines

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Geometric Hashing with Local Affine Frames

Geometric Hashing with Local Affine Frames

引用

conference on computer vision and pattern recognition (CVPR)

作者： O. Chum J. Matas Center for Machine Perception Czech Technical University Czech Republic CVSSP University of Surrey Guildford UK

We propose a novel representation of local image structure and a matching scheme that are insensitive to a wide range of appearance changes. The representation is a collection of local affine frames that are constructed on outer boundaries of maximally stable extremal regions (MSERS) in an affine-covariant way. Each local affine frame is described by a relative location of other local affine frames in its neighborhood. The image is thus represented by quantities that depend only on the location of the boundaries of MSERs. Inter-image correspondences between local affine frames are formed in constant time by geometric hashing. Direct detection of local afine frames removes the requirement of a point-based hashing to establish reference frames in a combinatorial way, which has in the case of affine transform complexily that is cubic in the number of points. Local affine frames, which are also the quantities represented in the hash table, occupy a 6 0 space and hence data collisions are less likely compared with 2 0 point hashing. Experimentally, the robustness of the method and its insensitiviq to photometric changes is demonstrated on images from different spectral bands of satellite sensor; on images of a transparent object and on images of an object taken during day and night.

关键词： Image recognition Photometry Image retrieval Object recognition computer vision Information retrieval Robustness Satellites Application software Real time systems

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Tracking With Sobolev Active Contours

Tracking With Sobolev Active Contours

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conference on computer vision and pattern recognition (CVPR)

作者： G. Sundaramoorthi J.D. Jackson A. Yezzi A.C. Mennucci School of Electrical and Computer Engineering Georgia Institute of Technology USA Scuola Normale Superiore Italy

Recently proposed Sobolev active contours introduced a new paradigm for minimizing energies defined on curves by changing the traditional cost of perturbing a curve and thereby redefining their gradients. Sobolev active contours evolve more globally and are less attracted to certain intermediate local minima than traditional active contours. In this paper we analyze Sobolev active contours in the Fourier domain in order to understand their evolution across different scales. This analysis shows an important and useful behavior of Sobolev contours, namely, that they move successively from coarse to increasingly finer scale motions in a continuous manner. Along with other properties, the previous observation reveals that Sobolev active contours are ideally suited for tracking problems that use active contours. Our purpose in this work is to show how a variety of active contour based tracking methods can be significantly improved merely by evolving the active contours according to the Sobolev method.

关键词： Active contours Shape Costs Motion analysis Video sequences Image edge detection Robustness Deformable models

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Shape Guided Object Segmentation

Shape Guided Object Segmentation

引用

conference on computer vision and pattern recognition (CVPR)

作者： E. Borenstein J. Malik Division of Applied Mathematics Brown University USA Department of Electrical Engineering and Computer Science University of California Berkeley USA

We construct a Bayesian model that integrates topdown with bottom-up criteria, capitalizing on their relative merits to obtain figure-ground segmentation that is shape-specific and texture invariant. A hierarchy of bottom-up segments in multiple scales is used to construct a prior on all possible figure-ground segmentations of the image. This prior is used by our top-down part to query and detect object parts in the image using stored shape templates. The detected parts are integrated to produce a global approximation for the object’s shape, which is then used by an inference algorithm to produce the final segmentation. Experiments with a large sample of horse and runner images demonstrate strong figure-ground segmentation despite high object and background variability. The segmentations are robust to changes in appearance since the matching component depends on shape criteria alone. The model may be useful for additional visual tasks requiring labeling, such as the segmentation of multiple scene objects.

关键词： Shape Object segmentation Image segmentation Bayesian methods Object detection Approximation algorithms Inference algorithms Horses Robustness Labeling

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Reconstructing Occluded Surfaces Using Synthetic Apertures: Stereo, Focus and Robust Measures

Reconstructing Occluded Surfaces Using Synthetic Apertures: ...

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conference on computer vision and pattern recognition (CVPR)

作者： V. Vaish M. Levoy R. Szeliski C.L. Zitnick Sing Bing Kang Computer Science Department University of Stanford CA USA Microsoft Research Limited Redmond WA USA

Most algorithms for 3D reconstruction from images use cost functions based on SSD, which assume that the surfaces being reconstructed are visible to all cameras. This makes it difficult to reconstruct objects which are partially occluded. Recently, researchers working with large camera arrays have shown it is possible to "see through" occlusions using a technique called synthetic aperture focusing. This suggests that we can design alternative cost functions that are robust to occlusions using synthetic apertures. Our paper explores this design space. We compare classical shape from stereo with shape from synthetic aperture focus. We also describe two variants of multi-view stereo based on color medians and entropy that increase robustness to occlusions. We present an experimental comparison of these cost functions on complex light fields, measuring their accuracy against the amount of occlusion.

关键词： Surface reconstruction Robustness Image reconstruction Focusing Cost function Cameras Space exploration Shape Stereo image processing Entropy

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