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» Invariances in kernel methods: From samples to objects
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CVPR
2007
IEEE
14 years 11 months ago
Multi-Layer Background Subtraction Based on Color and Texture
In this paper, we propose a robust multi-layer background subtraction technique which takes advantages of local texture features represented by local binary patterns (LBP) and pho...
Jian Yao, Jean-Marc Odobez
SI3D
2005
ACM
14 years 2 months ago
Adaptive sampling of intersectable models exploiting image and object-space coherence
We present a sampling strategy and rendering framework for intersectable models, whose surface is implicitly defined by a black box intersection test that provides the location a...
Anders Adamson, Marc Alexa, Andrew Nealen
ICRA
2006
IEEE
148views Robotics» more  ICRA 2006»
14 years 3 months ago
Surface Patch Reconstruction via Curve Sampling
This paper introduces a method that reconstructs a surface patch by sampling along three concurrent curves on the surface with a touch sensor. These data curves, each lying in a d...
Yan-Bin Jia, Liangchuan Mi, Jiang Tian
CVPR
2008
IEEE
14 years 11 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
IROS
2009
IEEE
186views Robotics» more  IROS 2009»
14 years 3 months ago
A statistical approach to gas distribution modelling with mobile robots - The Kernel DM+V algorithm
— Gas distribution modelling constitutes an ideal application area for mobile robots, which – as intelligent mobile gas sensors – offer several advantages compared to station...
Achim J. Lilienthal, Matteo Reggente, Marco Trinca...