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NIPS
2001
13 years 8 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
EMMCVPR
2005
Springer
14 years 7 days ago
Learning Hierarchical Shape Models from Examples
Abstract. We present an algorithm for automatically constructing a decompositional shape model from examples. Unlike current approaches to structural model acquisition, in which on...
Alex Levinshtein, Cristian Sminchisescu, Sven J. D...
ICIP
2009
IEEE
13 years 4 months ago
An efficient and robust sequential algorithm for background estimation in video surveillance
Many computer vision algorithms such as object tracking and event detection assume that a background model of the scene under analysis is known. However, in many practical circums...
Vikas Reddy, Conrad Sanderson, Brian C. Lovell
ECCV
2008
Springer
14 years 8 months ago
Feature Correspondence Via Graph Matching: Models and Global Optimization
Abstract. In this paper we present a new approach for establishing correspondences between sparse image features related by an unknown non-rigid mapping and corrupted by clutter an...
Lorenzo Torresani, Vladimir Kolmogorov, Carsten Ro...
AAAI
2012
11 years 9 months ago
A Testbed for Learning by Demonstration from Natural Language and RGB-Depth Video
We are developing a testbed for learning by demonstration combining spoken language and sensor data in a natural real-world environment. Microsoft Kinect RGBDepth cameras allow us...
Young Chol Song, Henry A. Kautz