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» Discrete optimization in computer vision
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CVPR
2010
IEEE
15 years 11 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
183
Voted
STOC
2007
ACM
239views Algorithms» more  STOC 2007»
16 years 4 months ago
Approximating minimum bounded degree spanning trees to within one of optimal
In the MINIMUM BOUNDED DEGREE SPANNING TREE problem, we are given an undirected graph with a degree upper bound Bv on each vertex v, and the task is to find a spanning tree of min...
Mohit Singh, Lap Chi Lau
132
Voted
AI
2010
Springer
15 years 3 months ago
Optimal query complexity bounds for finding graphs
We consider the problem of finding an unknown graph by using two types of queries with an additive property. Given a graph, an additive query asks the number of edges in a set of ...
Sung-Soon Choi, Jeong Han Kim
ICCV
2009
IEEE
1119views Computer Vision» more  ICCV 2009»
16 years 8 months ago
Spectral clustering of linear subspaces for motion segmentation
This paper studies automatic segmentation of multiple motions from tracked feature points through spectral embedding and clustering of linear subspaces. We show that the dimensi...
Fabien Lauer, Christoph Schn¨orr
ICCV
2009
IEEE
16 years 8 months ago
Learning Pedestrian Dynamics from the Real World
In this paper we describe a method to learn parameters which govern pedestrian motion by observing video data. Our learning framework is based on variational mode learning and a...
Paul Scovanner, Marshall Tappen