Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Visual reconstruction
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Object recognition by computer: the role of geometric constraints
Object recognition by computer: the role of geometric constraints
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
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Iterative point matching for registration of free-form curves and surfaces
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Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Markov random field modeling in computer vision
Markov random field modeling in computer vision
A variational level set approach to multiphase motion
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Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fully projective formulation to improve the accuracy of Lowe's pose-estimation algorithm
Computer Vision and Image Understanding
International Journal of Computer Vision
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric methods and applications: for computer science and engineering
Geometric methods and applications: for computer science and engineering
A survey of free-form object representation and recognition techniques
Computer Vision and Image Understanding
Geometric computing with Clifford algebras: theoretical foundations and applications in computer vision and robotics
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation
International Journal of Computer Vision
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
International Journal of Computer Vision
International Journal of Computer Vision
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Shape Priors for Level Set Representations
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MOTION '02 Proceedings of the Workshop on Motion and Video Computing
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
Analysis of Orientation Problems Using Plucker Lines
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
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MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Pose and motion estimation from vision using dual quaternion-based extended kalman filtering
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Computer Vision and Image Understanding - Special issue on nonrigid image registration
Unsupervised Non-parametric Region Segmentation Using Level Sets
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Twist Based Acquisition and Tracking of Animal and Human Kinematics
International Journal of Computer Vision
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Natural Image Statistics for Natural Image Segmentation
International Journal of Computer Vision
Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation
International Journal of Computer Vision
Monocular model-based 3D tracking of rigid objects
Foundations and Trends® in Computer Graphics and Vision
Structure from motion for scenes without features
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Three-dimensional shape knowledge for joint image segmentation and pose estimation
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Variational principles, surface evolution, PDEs, level set methods, and the stereo problem
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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Model-Based Motion Capture for Crash Test Video Analysis
Proceedings of the 30th DAGM symposium on Pattern Recognition
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AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
Combined Registration Methods for Pose Estimation
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
FlexiStickers: photogrammetric texture mapping using casual images
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Signal Processing
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ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
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International Journal of Computer Vision
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International Journal of Computer Vision
Clustered stochastic optimization for object recognition and pose estimation
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Proceedings of the 29th DAGM conference on Pattern recognition
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RobVis'08 Proceedings of the 2nd international conference on Robot vision
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ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
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Pattern Recognition
SIAM Journal on Imaging Sciences
Level set segmentation based on local gaussian distribution fitting
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Robust pose estimation with 3d textured models
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
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Image and Vision Computing
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International Journal of Computer Vision
Simultaneous monocular 2d segmentation, 3d pose recovery and 3d reconstruction
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Pose refinement of transparent rigid objects with a stereo camera
Transactions on Computational Science XIX
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In this article we present the integration of 3-D shape knowledge into a variational model for level set based image segmentation and contour based 3-D pose tracking. Given the surface model of an object that is visible in the image of one or multiple cameras calibrated to the same world coordinate system, the object contour extracted by the segmentation method is applied to estimate the 3-D pose parameters of the object. Vice-versa, the surface model projected to the image plane helps in a top-down manner to improve the extraction of the contour. While common alternative segmentation approaches, which integrate 2-D shape knowledge, face the problem that an object can look very differently from various viewpoints, a 3-D free form model ensures that for each view the model can fit the data in the image very well. Moreover, one additionally solves the problem of determining the object's pose in 3-D space. The performance is demonstrated by numerous experiments with a monocular and a stereo camera system.