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» Imaging applications of stochastic minimal graphs
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TIP
2010
155views more  TIP 2010»
13 years 3 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
ICCV
2011
IEEE
12 years 5 months ago
Recursive MDL via Graph Cuts: Application to Segmentation
We propose a novel patch-based image representation that is useful because it (1) inherently detects regions with repetitive structure at multiple scales and (2) yields a paramete...
Lena Gorelick, Andrew Delong, Olga Veksler, Yuri B...
CVPR
2000
IEEE
13 years 9 months ago
Perceptual Grouping and Segmentation by Stochastic Clustering
We use cluster analysis as a unifying principle for problems from low, middle and high level vision. The clustering problem is viewed as graph partitioning, where nodes represent ...
Yoram Gdalyahu, Noam Shental, Daphna Weinshall
CVPR
2007
IEEE
14 years 7 months ago
Learning Dynamic Event Descriptions in Image Sequences
Automatic detection of dynamic events in video sequences has a variety of applications including visual surveillance and monitoring, video highlight extraction, intelligent transp...
Harini Veeraraghavan, Nikolaos Papanikolopoulos, P...
MM
2006
ACM
218views Multimedia» more  MM 2006»
13 years 11 months ago
SmartLabel: an object labeling tool using iterated harmonic energy minimization
Labeling objects in images is an essential prerequisite for many visual learning and recognition applications that depend on training data, such as image retrieval, object detecti...
Wen Wu, Jie Yang