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- Pedro F. Felzenszwalb, Daniel P. Huttenlocher
- International Journal of Computer Vision
- 2004

This paper addresses the problem of segmenting an image into regions. We define a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an efficient segmentation algorithm based on this predicate, and show that although this algorithm makes greedy decisions it produces… (More)

- Pedro F. Felzenszwalb, Daniel P. Huttenlocher
- International Journal of Computer Vision
- 2004

In this paper we present a computationally efficient framework for part-based modeling and recognition of objects. Our work is motivated by the pictorial structure models introduced by Fischler and Elschlager. The basic idea is to represent an object by a collection of parts arranged in a deformable configuration. The appearance of each part is modeled… (More)

- Pedro F. Felzenszwalb, David A. McAllester, Deva Ramanan
- 2008 IEEE Conference on Computer Vision and…
- 2008

This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007 challenge in ten out of twenty categories. The system relies heavily… (More)

- Pedro F. Felzenszwalb, Daniel P. Huttenlocher
- International Journal of Computer Vision
- 2004

Markov random field models provide a robust and unified framework for early vision problems such as stereo and image restoration. Inference algorithms based on graph cuts and belief propagation have been found to yield accurate results, but despite recent advances are often too slow for practical use. In this paper we present some algorithmic techniques… (More)

- Pedro F. Felzenszwalb, Ross B. Girshick, David A. McAllester
- 2010 IEEE Computer Society Conference on Computer…
- 2010

We describe a general method for building cascade classifiers from part-based deformable models such as pictorial structures. We focus primarily on the case of star-structured models and show how a simple algorithm based on partial hypothesis pruning can speed up object detection by more than one order of magnitude without sacrificing detection accuracy. In… (More)

- Pedro F. Felzenszwalb, Joshua D. Schwartz
- 2007 IEEE Conference on Computer Vision and…
- 2007

We describe a new hierarchical representation for two-dimensional objects that captures shape information at multiple levels of resolution. This representation is based on a hierarchical description of an object's boundary and can be used in an elastic matching framework, both for comparing pairs of objects and for detecting objects in cluttered images. In… (More)

We present a new graph-theoretic approach to the problem of image segmentation. Our method uses local criteria and yet produces results that reflect global properties of the image. We develop a framework that provides specific definitions of what it means for an image to be underor over-segmented. We then present an efficient algorithm for computing a… (More)

- Pedro F. Felzenszwalb, Daniel P. Huttenlocher
- Theory of Computing
- 2012

We describe linear-time algorithms for solving a class of problems that involve transforming a cost function on a grid using spatial information. These problems can be viewed as a generalization of classical distance transforms of binary images, where the binary image is replaced by an arbitrary function on a grid. Alternatively they can be viewed in terms… (More)

- David J. Crandall, Pedro F. Felzenszwalb, Daniel P. Huttenlocher
- 2005 IEEE Computer Society Conference on Computer…
- 2005

We present a class of statistical models for part-based object recognition that are explicitly parameterized according to the degree of spatial structure they can represent. These models provide a way of relating different spatial priors that have been used for recognizing generic classes of objects, including joint Gaussian models and tree-structured… (More)