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TIP
2002
131views more  TIP 2002»
13 years 5 months ago
Optimal edge-based shape detection
Abstract--We propose an approach to accurately detecting twodimensional (2-D) shapes. The cross section of the shape boundary is modeled as a step function. We first derive a one-d...
Hankyu Moon, Rama Chellappa, Azriel Rosenfeld
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 6 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
SENSYS
2006
ACM
13 years 11 months ago
Target tracking with binary proximity sensors: fundamental limits, minimal descriptions, and algorithms
We explore fundamental performance limits of tracking a target in a two-dimensional field of binary proximity sensors, and design algorithms that attain those limits. In particul...
Nisheeth Shrivastava, Raghuraman Mudumbai, Upamany...
CIVR
2007
Springer
247views Image Analysis» more  CIVR 2007»
13 years 12 months ago
Near-duplicate keyframe retrieval with visual keywords and semantic context
Near-duplicate keyframes (NDK) play a unique role in large-scale video search, news topic detection and tracking. In this paper, we propose a novel NDK retrieval approach by explo...
Xiao Wu, Wanlei Zhao, Chong-Wah Ngo
JCST
2008
124views more  JCST 2008»
13 years 5 months ago
Clustering by Pattern Similarity
The task of clustering is to identify classes of similar objects among a set of objects. The definition of similarity varies from one clustering model to another. However, in most ...
Haixun Wang, Jian Pei