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» Robust object detection scheme using feature selection
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CVIU
2010
429views more  CVIU 2010»
14 years 12 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
16 years 1 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 ...
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ICPR
2008
IEEE
15 years 6 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
15 years 5 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»
14 years 11 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