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ECCV
2010
Springer
13 years 9 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
ICMCS
1999
IEEE
141views Multimedia» more  ICMCS 1999»
14 years 1 months ago
Three-Dimensional Metamorphosis Using Multiplanar Representation
We introduce a novel method for three-dimensional metamorphosis between two polyhedral objects with different topologies. The 3D objects are represented as multiple 2D images and ...
Mahesh Ramasubramanian, Anurag Mittal

Publication
285views
13 years 3 months ago
Guiding Visual Surveillance by Tracking Human Attention
We describe a novel method for directing the attention of an automated surveillance system. Our starting premise is that the attention of people in a scene can be used as an indica...
Ben Benfold and Ian Reid
ICRA
2005
IEEE
146views Robotics» more  ICRA 2005»
14 years 2 months ago
Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head
— Imitation is a powerful mechanism for transferring knowledge from an instructor to a na¨ıve observer, one that is deeply contingent on a state of shared attention between the...
Aaron P. Shon, David B. Grimes, Chris Baker, Matth...
CVPR
2011
IEEE
13 years 4 months ago
Intrinsic Dense 3D Surface Tracking
This paper presents a novel intrinsic 3D surface distance and its use in a complete probabilistic tracking framework for dynamic 3D data. Registering two frames of a deforming 3D ...
Yun Zeng, Chaohui Wang, Yang Wang, David Gu, Dimit...