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» Learning a Sparse Representation for Object Detection
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ICDE
2008
IEEE
141views Database» more  ICDE 2008»
15 years 11 months ago
SPOT: A System for Detecting Projected Outliers From High-dimensional Data Streams
In this paper, we present a new technique, called Stream Projected Ouliter deTector (SPOT), to deal with outlier detection problem in high-dimensional data streams. SPOT is unique ...
Ji Zhang, Qigang Gao, Hai H. Wang
ICCV
2011
IEEE
13 years 9 months ago
Gaussian Process Regression Flow for Analysis of Motion Trajectories
Recognition of motions and activities of objects in videos requires effective representations for analysis and matching of motion trajectories. In this paper, we introduce a new r...
Kihwan Kim, Dongryeol Lee, Irfan Essa
80
Voted
ICIP
2008
IEEE
15 years 11 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram
85
Voted
CVPR
2003
IEEE
15 years 11 months ago
Representation and Detection of Deformable Shapes
We describe some techniques that can be used to represent and detect deformable shapes in images. The main difficulty with deformable template models is the very large or infinite...
Pedro F. Felzenszwalb
65
Voted
ICPR
2006
IEEE
15 years 10 months ago
Robust Appearance-based Tracking using a sparse Bayesian classifier
An appearance-based approach to track an object that may undergo appearance change is proposed. Unlike recent methods that store a detailed representation of object's appeara...
Kwan-Yee Kenneth Wong, Roberto Cipolla, Shu-Fai Wo...