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Displaying 1-13 out of 13 total
View-Based Recognition Using an Eigenspace Approximation to the Hausdorff Measure
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Daniel P. Huttenlocher, Ryan H. Lilien, Clark F. Olson
Issue Date:September 1999
pp. 951-955
<p><b>Abstract</b>—View-based recognition methods, such as those using eigenspace techniques, have been successful for a number of recognition tasks. Such approaches, however, are somewhat limited in their ability to recognize objects tha...
 
Generating sharp panoramas from motion-blurred videos
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Yunpeng Li, Sing Bing Kang, Neel Joshi, Steve M. Seitz, Daniel P. Huttenlocher
Issue Date:June 2010
pp. 2424-2431
In this paper, we show how to generate a sharp panorama from a set of motion-blurred video frames. Our technique is based on joint global motion estimation and multi-frame deblurring. It also automatically computes the duty cycle of the video, namely the p...
 
Composite Models of Objects and Scenes for Category Recognition
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By David J. Crandall, Daniel P. Huttenlocher
Issue Date:June 2007
pp. 1-8
This paper presents a method of learning and recognizing generic object categories using part-based spatial models. The models are multiscale, with a scene component that specifies relationships between the object and surroundingscene context, and an objec...
 
Beyond Trees: Common-Factor Models for 2D Human Pose Recovery
Found in: Computer Vision, IEEE International Conference on
By Xiangyang Lan, Daniel P. Huttenlocher
Issue Date:October 2005
pp. 470-477
Tree structured models have been widely used for determining the pose of a human body, from either 2D or 3D data. While such models can effectively represent the kinematic constraints of the skeletal structure, they do not capture additional constraints su...
 
Efficient Belief Propagation for Early Vision
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Pedro F. Felzenszwalb, Daniel P. Huttenlocher
Issue Date:July 2004
pp. 261-268
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph cuts and belief propagation yield accurate results, but despite recent advan...
 
Recognizing Three-Dimensional Objects by Comparing Two-Dimensional Images
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Daniel P. Huttenlocher, Liana M. Lorigo
Issue Date:June 1996
pp. 878
In this paper we address the problem of recognizing an object from a novel viewpoint, given a single ``model'' view of that object. As is common in model-based recognition, objects and images are represented as sets of feature points. We present an efficie...
 
SfM with MRFs: Discrete-Continuous Optimization for Large-Scale Structure from Motion
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By David J. Crandall,Andrew Owens,Noah Snavely,Daniel P. Huttenlocher
Issue Date:December 2013
pp. 2841-2853
Recent work in structure from motion (SfM) has built 3D models from large collections of images downloaded from the Internet. Many approaches to this problem use incremental algorithms that solve progressively larger bundle adjustment problems. These incre...
 
A Unified Spatio-Temporal Articulated Model for Tracking
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Xiangyang Lan, Daniel P. Huttenlocher
Issue Date:July 2004
pp. 722-729
Tracking articulated objects in image sequences remains a challenging problem, particularly in terms of the ability to localize the individual parts of an object given self-occlusions and changes in viewpoint. In this paper we propose a two-dimensional spa...
 
Learning for stereo vision using the structured support vector machine
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Yunpeng Li, Daniel P. Huttenlocher
Issue Date:June 2008
pp. 1-8
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be learnt automatically using the structured support vector machine. The learnin...
 
Integrating Color, Texture, and Geometry for Image Retrieval
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Nicholas R. Howe, Daniel P. Huttenlocher
Issue Date:June 2000
pp. 2239
This paper examines the problem of image retrieval from large, heterogeneous image databases. We present a technique that fulfills several needs identified by surveying recent research in the field. This technique fairly integrates a diverse and expandable...
 
Adaptive Bayesian Recognition in Tracking Rigid Objects
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Yuri Boykov, Daniel P. Huttenlocher
Issue Date:June 2000
pp. 2697
We present a framework for tracking rigid objects based on an adaptive recognition technique that incorporates dependencies between object features. At each frame, we find a maximum a posteriori (MAP) estimate of the object parameters that include position...
 
On dynamic Voronoi diagrams and the minimum Hausdorff distance for point sets under Euclidean motion in the plane
Found in: Proceedings of the eighth annual symposium on Computational geometry (SCG '92)
By Daniel P. Huttenlocher, Jon M. Kleinberg, Klara Kedem
Issue Date:June 1992
pp. 110-119
We show that the dynamic Voronoi diagram of k sets of points in the plane, where each set consists of m points moving rigidly, has complexity O(n2k2λs(k)) for some fixed s, where λs(n) is the maximum length of a (n, s) Davenport-Schinzel sequence...
     
The upper envelope of Voronoi surfaces and its applications
Found in: Proceedings of the seventh annual symposium on Computational geometry (SCG '91)
By Daniel P. Huttenlocher, Klara Kedem, Micha Sharir
Issue Date:June 1991
pp. 194-203
We are constructing a workbench for computational geometry. This is intended to provide a framework for the implementation, testing, demonstration and application of algorithms in computational geometry. The workbench is being written in Smalltalk/V using ...
     
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