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» Comparing distributions and shapes using the kernel distance
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CVPR
2005
IEEE
15 years 11 months ago
Using the Inner-Distance for Classification of Articulated Shapes
We propose using the inner-distance between landmark points to build shape descriptors. The inner-distance is defined as the length of the shortest path between landmark points wi...
Haibin Ling, David W. Jacobs
AAAI
2007
14 years 11 months ago
A Kernel Approach to Comparing Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a Reprod...
Arthur Gretton, Karsten M. Borgwardt, Malte J. Ras...
ICIP
1997
IEEE
15 years 11 months ago
Binary Shape Coding Using 1-D Distance Values from Baseline
Here we describe a baseline-based binary shape coding method in which arbitrarily shaped object is represented by the traced 1-D data from baseline and turning point (TP). The sha...
Shi Hwa Lee, Dae-Sung Cho, Yu-Shin Cho, Sehoon Son...
CONEXT
2008
ACM
14 years 11 months ago
High performance traffic shaping for DDoS mitigation
Distributed Denial of Service (DDoS) attack mitigation systems usually generate a list of filter rules in order to block malicious traffic. In contrast to this binary decision we ...
Markus Goldstein, Matthias Reif, Armin Stahl, Thom...
CVPR
2008
IEEE
14 years 11 months ago
Loose shape model for discriminative learning of object categories
We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent ...
Margarita Osadchy, Elran Morash