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Estimation of Human Figure Motion Using Robust Tracking of Articulated Layers

Estimation of Human Figure Motion Using Robust Tracking of A...

引用

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

作者： Kooksang Moon V. Pavlovic Department of Computer Science Rutgers University Piscataway NJ USA

We propose a probabilistic method for tracking articulated objects, such as the human figure, across multiple layers in monocular image sequence. In this method, each link of a probabilistic articulated object is assigned to one individual image layer. The layered representation allows us to robustly model the pose and occlusion of object parts during its motion. Appearance of links is described in terms of learned statistics of basic image features, such as color, and geometric models of robust spatial kernels. This results in a highly efficient computational method for inference of the object’s pose. We apply this approach to tracking of the human figure in monocular video sequences. We show that the proposed method, coupled with a learned dynamic model, can lead to a robust articulated object tracker.

关键词： Motion estimation Humans Robustness Tracking Image sequences Kernel Focusing Parametric statistics Computational efficiency Biological system modeling

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Globally Optimal Grouping for Symmetric Boundaries

Globally Optimal Grouping for Symmetric Boundaries

引用

conference on computer vision and pattern recognition (CVPR)

作者： J.S. Stahl Song Wang Department of Computer Science and Engineering University of South Carolina Columbia SC USA

Many natural and man-made structures have a boundary that shows certain level of bilateral symmetry, a property that has been used to solve many computer-vision tasks. In this paper, we present a new grouping method for detecting closed boundaries with symmetry. We first construct a new type of grouping token in the form of a symmetric trapezoid, with which we can flexibly incorporate various boundary and region information into a unified grouping cost function. Particularly, this grouping cost function integrates Gestalt laws of proximity, closure, and continuity, besides the desirable boundary symmetry. We then develop a graph algorithm to find the boundary that minimizes this grouping cost function in a globally optimal fashion. Finally, we test this method by some experiments on a set of natural and medical images.

关键词： Cost function Image segmentation Joining processes computer vision computer science Medical tests Biomedical imaging Engine cylinders Image analysis Data mining

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Towards understanding what makes 3D objects appear simple or complex

Towards understanding what makes 3D objects appear simple or...

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

作者： Sreenivas R. Sukumar David L. Page Andreas F. Koschan Mongi A. Abidi Imaging Robotics and Intelligent Systems Laboratory University of Tennessee Knoxville USA

Humans perceive some objects more complex than others and learning or describing a particular object is directly related to the judged complexity. Towards the goal of understanding why the geometry of some 3D objects appear more complex than others, we conducted a psychophysical study and identified contributing attributes. Our experiments conclude that surface variation, symmetry, part count, simpler part decomposability, intricate details and topology are six significant dimensions that influence 3D visual shape complexity. With that knowledge, we present a method of quantifying complexity and show that the informational aspect of Shannonpsilas theory agrees with the human notion of shape complexity.

关键词： Humans computer vision Shape measurement Layout Size measurement Intelligent robots Image analysis Surface morphology Intelligent systems computer aided engineering

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Motion trajectories

Motion trajectories

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conference on computer vision and pattern recognition (CVPR)

作者： M. Shah K. Rangarajan P.-S. Tsai Computer Science Department University of Central Florida Orlando FL USA

A simple algorithm for selecting and linking interesting flow vectors across a sequence of frames for computing motion trajectories is presented. Tokens that have both interesting pixel gray values in the spatial domain and in the optical flow field in the temporal domain are tracked. This AND operation effectively removes some redundant trajectories. Due to errors introduced during the computation of optical flow, and the linking of such flow vectors across a sequence of frames, the resultant trajectories are not always smooth. A Kalman-filtering-based approach for smoothing the trajectories is discussed.< >

关键词： Image motion analysis Optical filters Optical computing Optical sensors Joining processes computer science Image sequences Layout Kalman filters Filtering

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Multimodal segmentation of medical images with heavily missing data

Multimodal segmentation of medical images with heavily missi...

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2021 ieee EMBS International conference on Biomedical and Health Informatics, BHI 2021

作者： Akbar, Muhammad Usman Murino, Vittorio Sona, Diego Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy Department of Electrical Electronics and Telecommunication Engineering degli Studi di Genova Genova Italy Huawei Technologies Ltd. Ireland Research Center Dublin Ireland Department of Computer Science Università di Verona Verona Italy Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy Data Science for Health Center for Digital Health & Wellbeing Fondazione Bruno Kessler Trento Italy

ISBN: (纸本)9781665403580

An important aim of research in medical imaging is the development of computer aided diagnosis (CAD) systems. A fundamental step in these systems is the image segmentation and convolutional neural networks (CNNs) are becoming the most commonly used approach to solve this task. However, despite their great power, in this domain CNNs are limited in their potential performance by the usually small amount of data [1]. Computed tomography (CT) and magnetic resonance imaging (MRI) scans are often used to examine the internal structure of human body and have their own unique properties and limitations. As a common practice, the investigations are usually done on a single modality, nonetheless, the simultaneous analysis of multiple modalities can significantly boost the segmentation accuracy. However, obtaining multiple imaging modalities for the same subject is very unlikely. In this paper we investigate the possibility of generating a multimodal CT-MRI representation for a segmentation task starting from a single modality, either CT or MRI. We considered this as a missing data problem, hence, we designed a pipeline where a CycleGAN was used to generate the missing modality. The synthetic modality was then paired with the real one to perform the required segmentation taking advantage of the multimodal representation and the augmented training dataset. To test the system we used two unrelated labeled datasets, one with CT data and the other one with MRI data. Results show that data enrichment with synthetic modalities improves the segmentation performance. © 2021 ieee

关键词： Magnetic resonance imaging

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Dominant orientation templates for real-time detection of texture-less objects

Dominant orientation templates for real-time detection of te...

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conference on computer vision and pattern recognition (CVPR)

作者： Stefan Hinterstoisser Vincent Lepetit Slobodan Ilic Pascal Fua Nassir Navab Department of Computer Science CAMP Technische Universität München Germany Computer Vision Laboratory Ecole Polytechnique Fédérale de Lausanne Switzerland

We present a method for real-time 3D object detection that does not require a time consuming training stage, and can handle untextured objects. At its core, is a novel template representation that is designed to be robust to small image transformations. This robustness based on dominant gradient orientations lets us test only a small subset of all possible pixel locations when parsing the image, and to represent a 3D object with a limited set of templates. We show that together with a binary representation that makes evaluation very fast and a branch-and-bound approach to efficiently scan the image, it can detect untextured objects in complex situations and provide their 3D pose in real-time.

关键词： Object detection computer vision Robustness Distortion measurement Runtime Histograms computer science Laboratories Testing Pixel

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Hand segmentation using learning-based prediction and verification for hand sign recognition

Hand segmentation using learning-based prediction and verifi...

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conference on computer vision and pattern recognition (CVPR)

作者： Y. Cui J.J. Weng Department of Computer Science Michigan State University East Lansing MI USA

This paper presents a prediction-and-verification segmentation scheme wing attention images from multiple fixations. A major advantage of this scheme is that it can handle a large number of different deformable objects presented in complex backgrounds. The scheme is also relatively efficient since the segmentation is guided by the past knowledge through a prediction-and-verification scheme. The system has been tested to segment hands in the sequences of intensity images, where each sequence represents a hand sign. The experimental result showed a 95% correct segmentation rate with a 3% false rejection rate.

关键词： Image segmentation Image reconstruction Interference computer science System testing Man machine systems Image motion analysis Image sequence analysis Motion analysis Data mining

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Degeneracies, dependencies and their implications in multi-body and multi-sequence factorizations

Degeneracies, dependencies and their implications in multi-b...

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conference on computer vision and pattern recognition (CVPR)

作者： L. Zelnik-Manor M. Irani Department of Computer Science and Applied Math Weizmann Institute of Science Rehovot Israel

The body of work on multi-body factorization separates between objects whose motions are independent. In this work we show that in many cases objects moving with different 3D motions will be captured as a single object using these approaches. We analyze what causes these degeneracies between objects and suggest an approach for overcoming some of them. We further show that in the case of multiple sequences linear dependencies can supply information for temporal synchronization of sequences and for spatial matching of points across sequences.

关键词： Layout Character generation Cameras Shape Bismuth computer science Subspace constraints Video sequences Stacking

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Toward a stratification of Helmholtz stereopsis

Toward a stratification of Helmholtz stereopsis

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conference on computer vision and pattern recognition (CVPR)

作者： T.E. Zickler P.N. Belhumeur D.J. Kriegman Electrical Engineering Yale University New Heaven CT USA Computer Science Columbia University New York NY USA Computer Science and Engineering University of California San Diego La Jolla CA USA

Helmholtz stereopsis has been previously introduced as a surface reconstruction technique that does not assume a model of surface reflectance. This technique relies on the use of multiple cameras and light sources, and it has been shown to be effective when the camera and source positions are known. Here, we take a stratified look at uncalibrated Helmholtz stereopsis. We derive a photometric matching constraint that can be used to establish correspondence without any knowledge of the cameras and sources (except that they are co-located), and we determine conditions under which we can obtain affine and metric reconstructions. An implementation and experimental results are presented.

关键词： Cameras Photometry Lighting Stereo vision Light sources Image reconstruction Surface reconstruction Reflectivity Shape computer society

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Affine trackability aids obstacle detection

Affine trackability aids obstacle detection

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conference on computer vision and pattern recognition (CVPR)

作者： H.S. Sawhney A.R. Hanson Department of Computer Science University of Massachusetts Amherst Amherst MA USA

Potential obstacles in the path of a mobile robot that can often be characterized as shallow (i.e., their extent in depth is small compared to their distance from the camera) are considered. The constraint of affine trackability is applied to automatic identification and 3-D reconstruction of shallow structures in realistic scenes. It is shown how this approach can handle independent object motion, occlusion, and motion discontinuity. Although the reconstructed structure is only a frontal plane approximation to the corresponding real structure, the robustness of depth of the approximation might be useful for obstacle avoidance, where the exact shape of an object may not be of consequence so long as collisions with it can be avoided.< >

关键词： Acquired immune deficiency syndrome Layout Image reconstruction Mobile robots Aggregates Image segmentation Tracking computer science Navigation Floors

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