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» Pruning Training Sets for Learning of Object Categories
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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 9 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
VMV
2008
107views Visualization» more  VMV 2008»
13 years 10 months ago
Learning with Few Examples using a Constrained Gaussian Prior on Randomized Trees
Machine learning with few training examples always leads to over-fitting problems, whereas human individuals are often able to recognize difficult object categories from only one ...
Erik Rodner, Joachim Denzler
ECCV
2010
Springer
13 years 11 months ago
Depth-Encoded Hough Voting for joint object detection and shape recovery
Detecting objects, estimating their pose and recovering 3D shape information is a critical problem in many vision and robotics applications. This paper addresses the above needs by...
CVPR
2006
IEEE
14 years 3 months ago
Depth from Familiar Objects: A Hierarchical Model for 3D Scenes
We develop an integrated, probabilistic model for the appearance and three-dimensional geometry of cluttered scenes. Object categories are modeled via distributions over the 3D lo...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
SI3D
2006
ACM
14 years 3 months ago
Human motion estimation from a reduced marker set
Motion capture data from human subjects exhibits considerable redundancy. In this paper, we propose novel methods for exploiting this redundancy. In particular, we set out to find...
Guodong Liu, Jingdan Zhang, Wei Wang 0010, Leonard...