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CVPR
2005
IEEE
15 years 11 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2008
IEEE
15 years 11 months ago
Action recognition by learning mid-level motion features
This paper presents a method for human action recognition based on patterns of motion. Previous approaches to action recognition use either local features describing small patches...
Alireza Fathi, Greg Mori
ICCV
2003
IEEE
15 years 11 months ago
Object Recognition with Informative Features and Linear Classification
In this paper we show that efficient object recognition can be obtained by combining informative features with linear classification. The results demonstrate the superiority of in...
Michel Vidal-Naquet, Shimon Ullman
CVPR
2010
IEEE
15 years 5 months ago
The Role of Features, Algorithms and Data in Visual Recognition
There are many computer vision algorithms developed for visual (scene and object) recognition. Some systems focus on involved learning algorithms, some leverage millions of trainin...
Devi Parikh and C. Lawrence Zitnick
ECCV
2008
Springer
15 years 11 months ago
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features
Viewpoint invariant pedestrian recognition is an important yet under-addressed problem in computer vision. This is likely due to the difficulty in matching two objects with unknown...
Douglas Gray, Hai Tao