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» A Sparse and Locally Shift Invariant Feature Extractor Appli...
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ICDAR
2007
IEEE
10 years 6 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun
EUROS
2006
224views Robotics» more  EUROS 2006»
10 years 3 months ago
Metric Localization with Scale-Invariant Visual Features Using a Single Perspective Camera
Abstract. The Scale Invariant Feature Transform (SIFT) has become a popular feature extractor for vision-based applications. It has been successfully applied to metric localization...
Maren Bennewitz, Cyrill Stachniss, Wolfram Burgard...
SAC
2010
ACM
10 years 6 months ago
Seal object detection in document images using GHT of local component shapes
Due to noise, overlapped text/signature and multi-oriented nature, seal (stamp) object detection involves a difficult challenge. This paper deals with automatic detection of seal ...
Partha Pratim Roy, Umapada Pal, Josep Lladó...
PAMI
2007
101views more  PAMI 2007»
9 years 11 months ago
A Thousand Words in a Scene
— This paper presents a novel approach for visual scene modeling and classification, investigating the combined use of text modeling methods and local invariant features. Our wo...
Pedro Quelhas, Florent Monay, Jean-Marc Odobez, Da...
ICIP
2008
IEEE
10 years 6 months ago
Hardware-friendly descreening
Conventional electrophotographic printers tend to produce Moir´e artifacts when used for printing images scanned from printed material such as books and magazines. We propose a n...
Hasib Siddiqui, Mireille Boutin, Charles A. Bouman
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