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» Tracking the Invisible: Learning Where the Object Might be
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CVPR
2007
IEEE
15 years 4 months ago
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Qian Yu, Gérard G. Medioni, Isaac Cohen
ICCV
2011
IEEE
13 years 1 months ago
Action Recognition in Videos Acquired by a Moving Camera Using Motion Decomposition of Lagrangian Particle Trajectories
Recognition of human actions in a video acquired by a moving camera typically requires standard preprocessing steps such as motion compensation, moving object detection and object ...
Shandong Wu, Omar Oreifej, and Mubarak Shah
ECCV
2010
Springer
14 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
115
Voted
CVPR
2003
IEEE
15 years 11 months ago
Activity Recognition Using the Dynamics of the Configuration of Interacting Objects
Monitoring activities using video data is an important surveillance problem. A special scenario is to learn the pattern of normal activities and detect abnormal events from a very...
Namrata Vaswani, Amit K. Roy Chowdhury, Rama Chell...
COLT
2003
Springer
15 years 2 months ago
On Finding Large Conjunctive Clusters
We propose a new formulation of the clustering problem that differs from previous work in several aspects. First, the goal is to explicitly output a collection of simple and meani...
Nina Mishra, Dana Ron, Ram Swaminathan