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» Covariant Derivatives and Vision
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ICPR
2010
IEEE
13 years 7 months ago
Matching Groups of People by Covariance Descriptor
In this paper, we present a new solution to the problem of matching groups of people across multiple nonoverlapping cameras. Similar to the problem of matching individuals across ...
Yinghao Cai, Valtteri Takala, Matti Pietikäin...
CVPR
2012
IEEE
11 years 10 months ago
Learning sparse covariance patterns for natural scenes
For scene classification, patch-level linear features do not always work as well as handcrafted features. In this paper, we present a new model to greatly improve the usefulness ...
Liwei Wang, Yin Li, Jiaya Jia, Jian Sun, David Wip...
ICPR
2008
IEEE
14 years 9 months ago
Using covariance matrices for unsupervised texture segmentation
In this paper we propose an efficient unsupervised texture segmentation method. We introduce the extension of a state-of-the-art segmentation algorithm, which is exclusively based...
Horst Bischof, Michael Donoser
ICPR
2008
IEEE
14 years 2 months ago
A study of semi-tied covariance modeling for online handwritten Chinese character recognition
This paper presents a new approach to largevocabulary online handwritten Chinese character recognition based on semi-tied covariance (STC) modeling. Detailed procedures are descri...
Yongqiang Wang, Qiang Huo
ACIVS
2006
Springer
14 years 2 months ago
Alternative Fuzzy Clustering Algorithms with L1-Norm and Covariance Matrix
In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the best known and most used method. Although FCM is a very useful method, it is sensitive to noise and outliers so that W...
Miin-Shen Yang, Wen-Liang Hung, Tsiung-Iou Chung