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检索条件"任意字段=Proceedings of the Workshop on Physics-Based Modeling in Computer Vision"

共 521 条记录，以下是461-470 订阅

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A vision system for observing and extracting facial action parameters

A vision system for observing and extracting facial action p...

引用

IEEE computer Society Conference on computer vision and Pattern Recognition workshops (CVPRW)

作者： Essa Pentland Perceptual Computing Section The Media Laboratory Massachusetts Institute of Technology Cambridge MA USA

We describe a computer vision system for observing the "action units" of a face using video sequences as input. The visual observation (sensing) is achieved by using an optimal estimation optical flow method coupled with a geometric and a physical (muscle) model describing the facial structure. This modeling results in a time-varying spatial patterning of facial shape and a parametric representation of the independent muscle action groups, responsible for the observed facial motions. These muscle action patterns may then be used for analysis, interpretation, and synthesis. Thus, by interpreting facial motions within a physics-based optimal estimation framework, a new control model of facial movement is developed. The newly extracted action units (which we name "FACS+") are both physics and geometry-based, and extend the well-known FACS parameters for facial expressions by adding temporal information and non-local spatial patterning of facial motion.< >

关键词： Machine vision Muscles Image analysis Psychology Feature extraction

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Deformable models with parameter functions: application to heart-wall modeling

Deformable models with parameter functions: application to h...

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IEEE computer Society Conference on computer vision and Pattern Recognition workshops (CVPRW)

作者： Park Metaxas Young Department of Computer & Information Science University of Pennsylvania Philadelphia PA USA Department of Radiology University of Pennsylvania Philadelphia PA USA

This paper develops a new class of physics-based deformable models which can deform both globally and locally. Their global parameters are functions allowing the definition of new parameterized primitives and parameterized global deformations. These new global parameter functions improve the accuracy of shape description through the use of a few intuitive parameters such as functional bending and twisting. Using a physics-based approach we convert these geometric models into deformable models that deform due to forces exerted from the data-points so as to conform to the given dataset. We present an experiment involving the extraction of shape and motion of the Left Ventricle (LV) of a heart from MRI-SPAMM data based on a few global parameter functions.< >

关键词： Biomedical imaging, MRI Machine vision Image processing Biomedical imaging Cardiography

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Physically-based combinations of views: representing rigid and nonrigid motion

Physically-based combinations of views: representing rigid a...

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IEEE workshop on Motion of Non-Rigid and Articulated Objects

作者： S. Sclaroff A.P. Pentland Computer Science Department Boston University Boston MA USA Perceptual Computing Section MIT Media Laboratory Cambridge MA USA

Nonrigid motion can be described as morphing or blending between extremal shapes, e.g. heart motion can be described as transitioning between the systole and diastole states. Using physically-based modeling techniques, shape similarity can be measured in terms of forces and strain. This provides a physically-based coordinate system in which motion is characterized in terms of physical similarity to a set of extremal shapes. Having such a low-dimensional characterization of nonrigid motion allows for the recognition and the comparison of different types of nonrigid motion.< >

关键词： Shape measurement Strain measurement computer graphics Proposals physics computer science Heart Force measurement Character recognition Geometry

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Parallelizing sequential programs by algorithm-level transformations

Parallelizing sequential programs by algorithm-level transfo...

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IEEE workshop on Program Comprehension

作者： S. Bhansali J.R. Hagemeister C.S. Raghavendra H. Sivaraman School of Electrical Engineering and Computer Science Washington State University Pullman WA USA

We address a significant problem in parallel processing research, namely, how to port existing sequential programs to run efficiently on parallel machines (the "dusty deck" problem). Conventional domain-independent techniques are inadequate for solving this problem because they miss significant opportunities of parallelism. We present experimental evidence to support our claim, analyze why current techniques are inadequate, and propose a knowledge-based reverse engineering approach for attacking this problem.< >

关键词： Parallel processing Parallel machines Concurrent computing computer aided manufacturing computer vision Application software Reverse engineering physics computing computer science Biochemical analysis

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Articulated and elastic non-rigid motion: a review

Articulated and elastic non-rigid motion: a review

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IEEE workshop on Motion of Non-Rigid and Articulated Objects

作者： J.K. Aggarwal Q. Cai W. Liao B. Sabata Department of Electrical and Computer Engineering Computer and Vision Research Center University of Texas Austin Austin TX USA University of Texas at Austin Austin TX US Dept. of Electr. & Comput. Eng. Texas Univ. Austin TX USA

Motion of physical objects is non-rigid, in general. Most researchers have focused on the study of the motion and structure of rigid objects because of its simplicity and elegance. Recently, investigation of non-rigid structure and motion transformation has drawn the attention of researchers from a wide spectrum of disciplines. Since the non-rigid motion class encompasses a huge domain, we restrict our overview to the motion analysis of articulated and elastic non-rigid objects. Numerous approaches that have been proposed to recover the 3D structure and motion of objects are studied. The discussion includes both: 1) motion recovery without shape models, and 2) model-based analysis, and covers a number of examples of real world objects.< >

关键词： Motion analysis computer vision Shape Heart Humans Taxonomy Contracts Classification tree analysis physics computing Biomedical imaging

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Active motion-based segmentation of human body outlines

Active motion-based segmentation of human body outlines

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IEEE workshop on Motion of Non-Rigid and Articulated Objects

作者： I.A. Kakadiaris D. Metaxas R. Bajcsy GRASP Laboratory Department of Computer and Information Science University of Pennsylvania Philadelphia PA USA

We present an integrated approach towards the segmentation and shape estimation of human body outlines. Initially, we assume that the human body consists of a single part, and we fit a deformable model to the given data using our physics-based shape and motion estimation framework. As an actor attains different postures, new protrusions emerge on the outline. We model these changes in the shape using a new representation scheme consisting of a parametric composition of deformable models. This representation allows us to identify the underlying human parts that gradually become visible, by monitoring the evolution of shape and motion parameters of the composed models. based on these parameters, their joint locations are identified. The algorithm is applied iteratively over subsequent frames until all moving parts are identified. We demonstrate the technique in a series of experiments with very encouraging results.< >

关键词： Humans Shape Deformable models Motion estimation Biological system modeling Motion analysis Joints Condition monitoring Application software Laboratories

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Lower limb kinematics of human walking with the medial axis transformation

Lower limb kinematics of human walking with the medial axis ...

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IEEE workshop on Motion of Non-Rigid and Articulated Objects

作者： A.G. Bharatkumar K.E. Daigle M.G. Pandy Qin Cai J.K. Aggarwal Computer and Vision Research Center University of Texas Austin Austin TX USA Kinesiology Biomechanics Laboratory University of Texas Austin Austin TX USA

The paper describes a simple model for free-speed human walking and compares ordinary images of a walking person to the model. Three dimensional kinematic data were obtained from subjects walking with markers over the joints of their limbs. The average of these data was used to derive a model stick figure of the lower limbs, based on the average anthropometric data of the population. Stick figures were obtained from ordinary images of persons dressed in tight fitting clothes without any markers by using the medial axis transformation. The two dimensional information from the image stick figures was compared with the projection of the three dimensional information of the model onto the relevant plane. A high degree of correlation was noted between the rotational patterns of the model and image stick figures.< >

关键词： Kinematics Humans Legged locomotion Biological system modeling Kinetic theory Frequency Thigh Leg Foot Motion analysis

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MULTISTRATEGY MACHINE LEARNING vision SYSTEM 21

MULTISTRATEGY MACHINE LEARNING VISION SYSTEM

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21ST AIPA workshop ON INTERDISCIPLINARY computer vision : AN EXPLORATION OF DIVERSE APPLICATIONS

作者： ROBERTS, B Honeywell Inc. (United States)

ISBN: (纸本)0819410438

Advances in the field of machine learning technology have yielded learning techniques with solid theoretical foundations that are applicable to the problems being encountered by object recognition systems. At Honeywell an object recognition system that works with high-level, symbolic, object features is under development. This system, named object recognition accomplished through combined learning expertise (ORACLE), employs both an inductive learning technique (i.e., conceptual clustering, CC) and a deductive technique (i.e., explanation-based learning, EBL) that are combined in a synergistic manner. This paper provides an overview of the ORACLE system, describes the machine learning mechanisms (EBL and CC) that it employs, and provides example results of system operation. The paper emphasizes the beneficial effect of integrating machine learning into object recognition systems.

关键词： Optical coherence tomography Electron beam lithography Object recognition Machine learning Data modeling Systems modeling Visual process modeling Feature extraction Machine vision Nose

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EFFICIENT SHAPE REPRESENTATION USING DEFORMABLE MODELS WITH LOCALLY ADAPTIVE FINITE-ELEMENTS

EFFICIENT SHAPE REPRESENTATION USING DEFORMABLE MODELS WITH ...

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CONF ON GEOMETRIC METHODS IN computer vision 2

作者： METAXAS, D KOH, EY Univ. of Pennsylvania (United States)

ISBN: (纸本)0819412805

This paper presents a physics-based algorithm to efficiently represent shape using deformable models with locally adaptive finite elements. We implement our technique using our previously developed dynamic deformable models which support local and global deformations. We express global deformations with a few parameters which represent the gross shape of an object, while local deformations capture shape details of objects through their many local parameters. Using triangular finite elements to represent local deformations our algorithm ensures that during subdivision the desirable finite element mesh properties of conformity, non-degeneracy, and smoothness are maintained. Through our algorithm, we locally subdivide the triangles used for the local deformations based on the distance between the given datapoints and the model. Furthermore, to improve our results we use a new algorithm to calculate the forces that datapoints exert on the model which is based on the minimal distance to a finite element instead of to a model node. In this way not only can we represent more accurately an object surface, but also more efficiently because new model nodes are added only when necessary in a local fashion. We present model fitting experiments to 3-D range data.

关键词： Data modeling 3D modeling Visual process modeling Chemical elements computer vision technology Machine vision Motion models Finite element methods Mathematical modeling Visualization

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'We do dishes, but we don't do windows': function-based modeling and recognition of rigid objects

'We do dishes, but we don't do windows': function-based mode...

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Intelligent Robots and computer vision XI: Algorithms, Techniques, and Active vision

作者： Sutton, Melanie Stark, Louise Bowyer, Kevin W. Univ. of South Florida Tampa FL USA

ISBN: (纸本)0819410268

Generic recognition for computer vision is a goal that is still far from reality. Part of the problem rests in the inherent limitations of current `model-based' vision. Our approach moves away from specific geometric or structural models and instead focuses on the functionality of the object as the property which drives the recognition process. This results in a representation that is generic in the sense of capturing an entire category of objects. One important assumption underlying the form and function approach is that a `small' number of `primitive' concepts about shape, physics, and causation will suffice to define the functionality of a broad range of categories. If multiple new `primitives' were required to define each additional category, then much of the advantages of the function-based approach over the traditional model-based approach would be lost. This paper presents some initial experimental results from the GRUFF-3 system, which uses function-based representation to recognize rigid objects in the superordinate category dishes. The performance of this system has been evaluated on a database of approximately 200 shapes.

关键词： computer vision

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