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» Robust object detection scheme using feature selection
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CVIU
2010
429views more  CVIU 2010»
13 years 7 months ago
Cascade of descriptors to detect and track objects across any network of cameras
Most multi-camera systems assume a well structured environment to detect and track objects across cameras. Cameras need to be fixed and calibrated, or only objects within a traini...
Alexandre Alahi, Pierre Vandergheynst, Michel Bier...
CVPR
2007
IEEE
14 years 9 months ago
Principal Curvature-Based Region Detector for Object Recognition
This paper presents a new structure-based interest region detector called Principal Curvature-Based Regions (PCBR) which we use for object class recognition. The PCBR interest ope...
Hongli Deng, Wei Zhang, Eric N. Mortensen, Thomas ...
ICPR
2008
IEEE
14 years 1 months ago
Robust outdoor text detection using text intensity and shape features
Recognizing texts from camera images is a known hard problem because of the difficulties in text segmentation from the varied and complicated backgrounds. In this paper, we propo...
Zongyi Liu, Sudeep Sarkar
CVPR
2005
IEEE
14 years 1 months ago
The Distinctiveness, Detectability, and Robustness of Local Image Features
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to i...
Gustavo Carneiro, Allan D. Jepson
TNN
2008
119views more  TNN 2008»
13 years 7 months ago
Selecting Useful Groups of Features in a Connectionist Framework
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
Debrup Chakraborty, Nikhil R. Pal