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» Monte Carlo Localization Using SIFT Features
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MOBICOM
2004
ACM
15 years 3 months ago
Localization for mobile sensor networks
Many sensor network applications require location awareness, but it is often too expensive to include a GPS receiver in a sensor network node. Hence, localization schemes for sens...
Lingxuan Hu, David Evans
95
Voted
DAC
2010
ACM
14 years 9 months ago
QuickYield: an efficient global-search based parametric yield estimation with performance constraints
With technology scaling down to 90nm and below, many yield-driven design and optimization methodologies have been proposed to cope with the prominent process variation and to incr...
Fang Gong, Hao Yu, Yiyu Shi, Daesoo Kim, Junyan Re...
ICASSP
2009
IEEE
15 years 4 months ago
Compression of image patches for local feature extraction
Local features are widely used for content-based image retrieval and object recognition. We present an efficient method for encoding digital images suitable for local feature extr...
Mina Makar, Chuo-Ling Chang, David M. Chen, Sam S....
ICMCS
2007
IEEE
223views Multimedia» more  ICMCS 2007»
15 years 3 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
80
Voted
ICIP
2008
IEEE
15 years 11 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram