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» Feature versus model based noise robustness
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ECCV
2002
Springer
14 years 9 months ago
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
We present a variational integration of nonlinear shape statistics into a Mumford?Shah based segmentation process. The nonlinear statistics are derived from a set of training silho...
Christoph Schnörr, Daniel Cremers, Timo Kohlb...
TCSV
2008
124views more  TCSV 2008»
13 years 7 months ago
A Block-Edge-Pattern-Based Content Descriptor in DCT Domain
In this correspondence, we describe a robust and effective content descriptor based on block edge patterns extracted directly in DCT domain, which is suitable for applications in J...
Jianmin Jiang, Kaijin Qiu, Guoqiang Xiao
ICASSP
2011
IEEE
12 years 11 months ago
Multi-cue based multi-target tracking using online random forests
Discriminative tracking has become popular tracking methods due to their descriptive power for foreground/background separation. Among these methods, online random forest is recen...
Xinchu Shi, Xiaoqin Zhang, Yang Liu, Weiming Hu, H...
ECCV
2010
Springer
14 years 1 months ago
Robust Multi-View Boosting with Priors
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
VLSM
2005
Springer
14 years 1 months ago
A Surface Reconstruction Method for Highly Noisy Point Clouds
In this paper we propose a surface reconstruction method for highly noisy and non-uniform data based on minimal surface model and tensor voting method. To deal with ill-posedness, ...
DanFeng Lu, HongKai Zhao, Ming Jiang 0001, ShuLin ...