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» Learning Photometric Invariance for Object Detection
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ICIAR
2009
Springer
14 years 7 months ago
Invariant Shape Matching for Detection of Semi-local Image Structures
Abstract. Shape features applied to object recognition has been actively studied since the beginning of the field in 1950s and remain a viable alternative to appearance based metho...
Lech Szumilas, Horst Wildenauer, Allan Hanbury
CVPR
2012
IEEE
12 years 12 months ago
Learning rotation-aware features: From invariant priors to equivariant descriptors
Identifying suitable image features is a central challenge in computer vision, ranging from representations for lowlevel to high-level vision. Due to the difficulty of this task,...
Uwe Schmidt, Stefan Roth
ICPR
2006
IEEE
15 years 10 months ago
Fast, Illumination Insensitive Face Detection Based on Multilinear Techniques and Curvature Features
This paper brings together two recent developments in image analysis. We consider a new mathematical framework that provides illumination invariant descriptors for face detection....
Christian Bauckhage, Thomas Käster
ICPR
2010
IEEE
14 years 11 months ago
An RST-Tolerant Shape Descriptor for Object Detection
In this paper, we propose a new object detection method that does not need a learning mechanism. Given a hand-drawn model as a query, we can detect and locate objects that are sim...
Chih-Wen Su, Mark Liao, Yu-Ming Liang, Hsiao-Rong ...
CVPR
2011
IEEE
14 years 4 months ago
Learning and Matching Multiscale Template Descriptors for Real-Time Detection, Localization and Tracking
We describe a system to learn an object template from a video stream, and localize and track the corresponding object in live video. The template is decomposed into a number of lo...
Taehee Lee, Stefano Soatto