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» Learning Photometric Invariance for Object Detection
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ICIAR
2009
Springer
14 years 11 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
13 years 3 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
16 years 2 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
15 years 3 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 8 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