Felzenszwalb, Pedro F. - Department of Computer Science, University of Chicago

• Hierarchical Matching of Deformable Shapes Pedro F. Felzenszwalb
• A Min-Cover Approach for Finding Salient Curves Pedro Felzenszwalb
• 2D Min-Filters with Polygons Paolo Codenotti and Pedro Felzenszwalb
• Fast Algorithms for LargeStateSpace HMMs with Applications to Web Usage Analysis
• Representation and Detection of Shapes in Images Pedro F. Felzenszwalb
• A MinCover Approach for Finding Salient Curves Pedro Felzenszwalb
• Ecient Matching of Pictorial Structures Pedro F. Felzenszwalb Daniel P. Huttenlocher
• 2D MinFilters with Polygons Paolo Codenotti and Pedro Felzenszwalb
• Fast Inference with Min-Sum Matrix Product Pedro F. Felzenszwalb
• Globally Optimal Pixel Labeling Algorithms for Tree Metrics Pedro F. Felzenszwalb
• Journal of Artificial Intelligence Research 29 (2007) 153-190 Submitted 10/06; published 06/07 The Generalized A* Architecture
• Efficient Belief Propagation for Early Vision Pedro F. Felzenszwalb
• Object Recognition by Combining Appearance and Geometry
• Representation and Detection of Deformable Shapes
• Object Detection Grammars Pedro F. Felzenszwalb and David McAllester
• Object Recognition by Combining Appearance and Geometry
• Object Detection with Discriminatively Trained Part Based Models
• Efficient Belief Propagation for Early Vision Pedro F. Felzenszwalb and Daniel P. Huttenlocher
• Journal of Artificial Intelligence Research 29 (2007) 153190 Submitted 10/06; published 06/07 The Generalized A* Architecture
• Representation and Detection of Shapes in Images Pedro F. Felzenszwalb
• Learning Models for Object Recognition Pedro F. Felzenszwalb
• Representation and Detection of Deformable Shapes Pedro F. Felzenszwalb
• Pictorial Structures for Object Recognition Pedro F. Felzenszwalb
• DIGIPAPER: A VERSATILE COLOR DOCUMENT IMAGE REPRESENTATION Daniel Huttenlocher and Pedro Felzenszwalb
• Cascade Object Detection with Deformable Part Models Pedro F. Felzenszwalb
• A Discriminatively Trained, Multiscale, Deformable Part Model Pedro Felzenszwalb
• Learning Models for Object Recognition Pedro F. Felzenszwalb
• Pictorial Structures for Object Recognition Pedro F. Felzenszwalb
• Fast Inference with Min-Sum Matrix Product Pedro F. Felzenszwalb
• Visibility Constraints on Features of 3D Objects Ronen Basri
• Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis
• Distance Transforms of Sampled Functions Pedro F. Felzenszwalb Daniel P. Huttenlocher
• Spatial Priors for Part-Based Recognition using Statistical Models David Crandall1
• Dynamic Programming and Graph Algorithms in Computer Vision Pedro F. Felzenszwalb and Ramin Zabih
• Efficient Belief Propagation for Early Vision Pedro F. Felzenszwalb
• Spatial Priors for PartBased Recognition using Statistical Models David Crandall 1 Pedro Felzenszwalb Daniel Huttenlocher
• Representation and Detection of Deformable Shapes
• Computing rank-convolutions with a mask Laszlo Babai and Pedro Felzenszwalb
• Distance Transforms of Sampled Functions Pedro F. Felzenszwalb Daniel P. Huttenlocher
• Hierarchical Matching of Deformable Shapes Pedro F. Felzenszwalb
• Tiered Scene Labeling with Dynamic Programming Pedro F. Felzenszwalb