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» Boosting Object Detection Using Feature Selection
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ICST
2010
IEEE
15 years 25 days ago
Satisfying Test Preconditions through Guided Object Selection
—A random testing strategy can be effective at finding faults, but may leave some routines entirely untested if it never gets to call them on objects satisfying their preconditi...
Yi Wei, Serge Gebhardt, Bertrand Meyer, Manuel Ori...
TMM
2008
126views more  TMM 2008»
15 years 2 months ago
Extraction of Audio Features Specific to Speech Production for Multimodal Speaker Detection
A method that exploits an information theoretic framework to extract optimized audio features using video information is presented. A simple measure of mutual information (MI) betw...
Patricia Besson, Vlad Popovici, Jean-Marc Vesin, J...
125
Voted
ICPR
2000
IEEE
15 years 6 months ago
Moving Shadow and Object Detection in Traffic Scenes
We present an algorithm for segmentation of traffic scenes that distinguishes moving objects from cast shadows. Three image features at each pixel site are considered: brightness,...
Ivana Mikic, Pamela C. Cosman, Greg T. Kogut, Moha...
ICCV
2009
IEEE
1198views Computer Vision» more  ICCV 2009»
16 years 7 months ago
Implicit Color Segmentation Features for Pedestrian Detection
We investigate the problem of pedestrian detection in still images. Sliding window classifiers, notably using the Histogram-of-Gradient (HOG) features proposed by Dalal and Trig...
Patrick Ott and Mark Everingham
150
Voted
ICIP
2007
IEEE
15 years 6 months ago
Real-Time Pedestrian Detection using Eigenflow
We propose a novel learning algorithm to detect moving pedestrians from a stationary camera in real-time. The algorithm learns a discriminative model based on eigenflow, i.e. the ...
Dhiraj Goel, Tsuhan Chen