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CLOR
2006
13 years 10 months ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Robert Fergus, Pietro Perona, Andrew Zisserman
ECCV
2004
Springer
14 years 8 months ago
A Visual Category Filter for Google Images
We extend the constellation model to include heterogeneous parts which may represent either the appearance or the geometry of a region of the object. The parts and their spatial co...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2007
IEEE
14 years 8 months ago
OPTIMOL: automatic Online Picture collecTion via Incremental MOdel Learning
A well-built dataset is a necessary starting point for advanced computer vision research. It plays a crucial role in evaluation and provides a continuous challenge to stateof-the-...
Li-Jia Li, Gang Wang, Fei-Fei Li 0002
VR
2003
IEEE
211views Virtual Reality» more  VR 2003»
14 years 5 hour ago
Editing Real World Scenes: Augmented Reality with Image-based Rendering
We present a method that using only an uncalibrated camera allows the capture of object geometry and appearance, and then at a later stage registration and AR overlay into a new s...
Dana Cobzas, Martin Jägersand, Keith Yerex
ICCV
2009
IEEE
14 years 11 months ago
Tracking in Unstructured Crowded Scenes
This paper presents a target tracking framework for unstructured crowded scenes. Unstructured crowded scenes are defined as those scenes where the motion of a crowd appears to b...
Mikel Rodriguez, Saad Ali, Takeo Kanade