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» Image Classification using Random Forests and Ferns
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ICCV
2007
IEEE
14 years 7 months ago
Image Classification using Random Forests and Ferns
We explore the problem of classifying images by the object categories they contain in the case of a large number of object categories. To this end we combine three ingredients: (i...
Andrew Zisserman, Anna Bosch, Xavier Muñoz
PAMI
2010
249views more  PAMI 2010»
13 years 3 months ago
Fast Keypoint Recognition Using Random Ferns
While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle pe...
Mustafa Özuysal, Michael Calonder, Vincent Le...
PAMI
2008
270views more  PAMI 2008»
13 years 5 months ago
Randomized Clustering Forests for Image Classification
This paper introduces three new contributions to the problems of image classification and image search. First, we propose a new image patch quantization algorithm. Other competitiv...
Frank Moosmann, Eric Nowak, Frédéric...
ICIP
2010
IEEE
13 years 3 months ago
A two-pass random forests classification of airborne lidar and image data on urban scenes
Random forests ensemble classifier showed to be suitable for classifying mutlisource data such as lidar and RGB image for urban scene mapping. However, two major problems remain :...
Li Guo, Nesrine Chehata, Samia Boukir
ICPR
2010
IEEE
13 years 9 months ago
Fast and Spatially-Smooth Terrain Classification Using Monocular Camera
In this paper, we present a monocular camera based terrain classification scheme. The uniqueness of the proposed scheme is that it inherently incorporates spatial smoothness while...
Chetan Jakkoju, Madhava Krishna, C. V. Jawahar