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» A Topic-Motion Model for Unsupervised Video Object Discovery
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ICCV
2011
IEEE
12 years 9 months ago
Discovering Object Instances from Scenes of Daily Living
We propose an approach to identify and segment objects from scenes that a person (or robot) encounters in Activities of Daily Living (ADL). Images collected in those cluttered sce...
Hongwen Kang, Martial Hebert, Takeo Kanade
ICPR
2006
IEEE
14 years 11 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen
CVPR
2011
IEEE
13 years 7 months ago
Learning Better Image Representations Using 'Flobject Analysis'
Unsupervised learning can be used to extract image representations that are useful for various and diverse vision tasks. After noticing that most biological vision systems for int...
Inmar Givoni, Patrick Li, Brendan Frey
ICPR
2006
IEEE
14 years 11 months ago
Activity Discovery from Surveillance Videos
Multi-agent interactions often result in mutual occlusion sequences which constitute a visual signature for the event. We define six qualitative occlusion primitives based on the ...
Amitabha Mukerjee, K. S. Venkatesh, Pabitra Mitra,...
ECCV
2008
Springer
14 years 11 months ago
Unsupervised Learning of Skeletons from Motion
Abstract. Humans demonstrate a remarkable ability to parse complicated motion sequences into their constituent structures and motions. We investigate this problem, attempting to le...
David A. Ross, Daniel Tarlow, Richard S. Zemel