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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
PAMI
2008
189views more  PAMI 2008»
13 years 7 months ago
Detecting Objects of Variable Shape Structure With Hidden State Shape Models
This paper proposes a method for detecting object classes that exhibit variable shape structure in heavily cluttered images. The term "variable shape structure" is used t...
Jingbin Wang, Vassilis Athitsos, Stan Sclaroff, Ma...
BMVC
2001
13 years 9 months ago
Adaptive Visual System for Tracking Low Resolution Colour Targets
This paper addresses the problem of using appearance and motion models in classifying and tracking objects when detailed information of the object’s appearance is not available....
Pakorn KaewTrakulPong, Richard Bowden
CVPR
2006
IEEE
14 years 9 months ago
Putting Objects in Perspective
Image understanding requires not only individually estimating elements of the visual world but also capturing the interplay among them. In this paper, we provide a framework for p...
Derek Hoiem, Alexei A. Efros, Martial Hebert
ICCV
2009
IEEE
2061views Computer Vision» more  ICCV 2009»
15 years 13 days ago
Background Subtraction for Freely Moving Cameras
Background subtraction algorithms define the background as parts of a scene that are at rest. Traditionally, these algorithms assume a stationary camera, and identify moving obj...
Yaser Sheikh, Omar Javed, Takeo Kanade