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» On the Performance of Clustering in Hilbert Spaces
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ICDE
2012
IEEE
343views Database» more  ICDE 2012»
11 years 10 months ago
Bi-level Locality Sensitive Hashing for k-Nearest Neighbor Computation
We present a new Bi-level LSH algorithm to perform approximate k-nearest neighbor search in high dimensional spaces. Our formulation is based on a two-level scheme. In the first ...
Jia Pan, Dinesh Manocha
ECCV
2006
Springer
14 years 9 months ago
A Multiview Approach to Tracking People in Crowded Scenes Using a Planar Homography Constraint
Occlusion and lack of visibility in dense crowded scenes make it very difficult to track individual people correctly and consistently. This problem is particularly hard to tackle i...
Saad M. Khan, Mubarak Shah
CIVR
2007
Springer
180views Image Analysis» more  CIVR 2007»
14 years 1 months ago
Probabilistic matching and resemblance evaluation of shapes in trademark images
We present a novel matching and similarity evaluation method for planar geometric shapes represented by sets of polygonal curves. Given two shapes, the matching algorithm randomly...
Helmut Alt, Ludmila Scharf, Sven Scholz
JIIS
2006
113views more  JIIS 2006»
13 years 7 months ago
Spatial ordering and encoding for geographic data mining and visualization
: Geographic information (e.g., locations, networks, and nearest neighbors) are unique and different from other aspatial attributes (e.g., population, sales, or income). It is a ch...
Diansheng Guo, Mark Gahegan
PAMI
2008
161views more  PAMI 2008»
13 years 7 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...