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» Comparing distributions and shapes using the kernel distance
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CVPR
2005
IEEE
14 years 7 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
13 years 7 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
14 years 6 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
13 years 7 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
13 years 7 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