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» Mercer Kernels for Object Recognition with Local Features
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NIPS
2008
15 years 5 months ago
Dimensionality Reduction for Data in Multiple Feature Representations
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
AAAI
1994
15 years 5 months ago
Applying VC-Dimension Analysis To 3D Object Recognition from Perspective Projections
We analyze the amount of information needed to carry out model-based recognition tasks, in the context of a probabilistic data collection model, and independently of the recogniti...
Michael Lindenbaum, Shai Ben-David
ACCV
2010
Springer
14 years 11 months ago
One-Class Classification with Gaussian Processes
Detecting instances of unknown categories is an important task for a multitude of problems such as object recognition, event detection, and defect localization. This paper investig...
Michael Kemmler, Erik Rodner, Joachim Denzler
CVPR
2011
IEEE
14 years 11 months ago
Proposal Generation for Object Detection using Cascaded Ranking SVMs
Object recognition has made great strides recently. However, the best methods, such as those based on kernelSVMs are highly computationally intensive. The problem of how to accele...
Ziming Zhang, Jonathan Warrell, Philip Torr
ICMCS
2007
IEEE
223views Multimedia» more  ICMCS 2007»
15 years 10 months ago
An Effective Local Invariant Descriptor Combining Luminance and Color Information
Extraction of stable local invariant features is very important in many computer vision applications, such as image matching, object recognition and image retrieval. Most existing...
Dong Zhang, Weiqiang Wang, Wen Gao, Shuqiang Jiang