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» New Appearance Models for Natural Image Matting
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ICIP
2010
IEEE
13 years 7 months ago
Gaussian mixture models for spots in microscopy using a new split/merge em algorithm
In confocal microscopy imaging, target objects are labeled with fluorescent markers in the living specimen, and usually appear as spots in the observed images. Spot detection and ...
Kangyu Pan, Anil C. Kokaram, Jens Hillebrand, Mani...
AAAI
2012
11 years 11 months ago
A Testbed for Learning by Demonstration from Natural Language and RGB-Depth Video
We are developing a testbed for learning by demonstration combining spoken language and sensor data in a natural real-world environment. Microsoft Kinect RGBDepth cameras allow us...
Young Chol Song, Henry A. Kautz
CVPR
2008
IEEE
14 years 11 months ago
Graph-shifts: Natural image labeling by dynamic hierarchical computing
In this paper, we present a new approach for image labeling based on the recently introduced graph-shifts algorithm. Graph-shifts is an energy minimization algorithm that does lab...
Jason J. Corso, Alan L. Yuille, Zhuowen Tu
CVPR
2008
IEEE
14 years 11 months ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen
ICASSP
2011
IEEE
13 years 1 months ago
Beyond bag of words: Combining generative and discriminative models for natural scene categorization
This paper proposes a simple yet new and effective framework by combining generative model and discriminative model for natural scene categorization. A state-of-the-art approach f...
Zhen Li, Kim-Hui Yap, Xiao-Ming Chen