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» Mercer Kernels for Object Recognition with Local Features
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CIVR
2006
Springer
129views Image Analysis» more  CIVR 2006»
15 years 8 months ago
Retrieving Objects Using Local Integral Invariants
The use of local features in computer vision has shown to be promising. Local features have several advantages including invariance to image transformations, independence of the ba...
Alaa Halawani, Hashem Tamimi
ICCV
2009
IEEE
1022views Computer Vision» more  ICCV 2009»
16 years 9 months ago
Kernelized Locality-Sensitive Hashing for Scalable Image Search
Fast retrieval methods are critical for large-scale and data-driven vision applications. Recent work has explored ways to embed high-dimensional features or complex distance fun...
Brian Kulis, Kristen Grauman
IBPRIA
2005
Springer
15 years 9 months ago
Gabor Parameter Selection for Local Feature Detection
Abstract. Some recent works have addressed the object recognition problem by representing objects as the composition of independent image parts, where each part is modeled with “...
Plinio Moreno, Alexandre Bernardino, José S...
ICCV
2007
IEEE
16 years 6 months ago
Visual Tracking by Affine Kernel Fitting Using Color and Object Boundary
Kernel-based trackers aggregate image features within the support of a kernel (a mask) regardless of their spatial structure. These trackers spatially fit the kernel (usually in l...
Ido Leichter, Michael Lindenbaum, Ehud Rivlin
CVPR
2009
IEEE
16 years 11 months ago
Fast concurrent object localization and recognition
Object localization and classification are important problems in computer vision. However, in many applications, exhaustive search over all class labels and image locations is co...
Tom Yeh, John J. Lee, Trevor Darrell