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ACCV
2006
Springer
14 years 1 months ago
A Multiscale Co-linearity Statistic Based Approach to Robust Background Modeling
Background subtraction is an essential task in several static camera based computer vision systems. Background modeling is often challenged by spatio-temporal changes occurring due...
Prithwijit Guha, Dibyendu Palai, K. S. Venkatesh, ...
MA
2010
Springer
135views Communications» more  MA 2010»
13 years 6 months ago
Nonparametric comparison of regression functions
In this work we provide a new methodology for comparing regression functions m1 and m2 from two samples. Since apart from smoothness no other (parametric) assumptions are required...
Ramidha Srihera, Winfried Stute

Publication
576views
15 years 7 months ago
Within-die Process Variations: How Accurately can They Be Statistically Modeled?
Within-die process variations arise during integrated circuit (IC) fabrication in the sub-100nm regime. These variations are of paramount concern as they deviate the performance of...
Brendan Hargreaves, Henrik Hult, Sherief Reda
ICCV
2007
IEEE
14 years 9 months ago
The Best of Both Worlds: Combining 3D Deformable Models with Active Shape Models
Reliable 3D tracking is still a difficult task. Most parametrized 3D deformable models rely on the accurate extraction of image features for updating their parameters, and are pro...
Christian Vogler, Zhiguo Li, Atul Kanaujia, Siome ...

Publication
336views
12 years 15 days ago
Feature Mining for Localised Crowd Counting
This paper presents a multi-output regression model for crowd counting in public scenes. Existing counting by regression methods either learn a single model for global counting, or...
Ke Chen, Chen Change Loy, Shaogang Gong, Tao Xiang...