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» Object detection using spatial histogram features
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DICTA
2003
13 years 10 months ago
Background Modeling and Subtraction Using a Local-linear-dependence-based Cauchy Statistical Model
:Many motion object detection algorithms rely on the process of background subtraction, an important technique which is used for detecting changes from a model of the background ...
Ying Ming, Jingjue Jiang, Jun Ming
ICPR
2008
IEEE
14 years 3 months ago
Directional entropy feature for human detection
In this paper we propose a novel feature, called directional entropy feature (DEF), to improve the performance of human detection under complicated background in images. DEF descr...
Long Meng, Liang Li, Shuqi Mei, Weiguo Wu
ICIP
2008
IEEE
14 years 10 months ago
Kernel-based high-dimensional histogram estimation for visual tracking
We propose an approach for non-rigid tracking that represents objects by their set of distribution parameters. Compared to joint histogram representations, a set of parameters suc...
Allen Tannenbaum, James G. Malcolm, Peter Karasev
ECCV
2008
Springer
14 years 10 months ago
Learning Spatial Context: Using Stuff to Find Things
The sliding window approach of detecting rigid objects (such as cars) is predicated on the belief that the object can be identified from the appearance in a small region around the...
Geremy Heitz, Daphne Koller
ECCV
2002
Springer
14 years 10 months ago
Resolution Selection Using Generalized Entropies of Multiresolution Histograms
The performances of many image analysis tasks depend on the image resolution at which they are applied. Traditionally, resolution selection methods rely on spatial derivatives of i...
Efstathios Hadjidemetriou, Michael D. Grossberg, S...