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GI
2007
Springer
13 years 10 months ago
Background Modeling Using Adaptive Cluster Density Estimation for Automatic Human Detection
: Detection is an inherent part of every advanced automatic tracking system. In this work we focus on automatic detection of humans by enhanced background subtraction. Background s...
Harish Bhaskar, Lyudmila Mihaylova, Simon Maskell
CVPR
2004
IEEE
14 years 6 months ago
Motion-Based Background Subtraction Using Adaptive Kernel Density Estimation
Background modeling is an important component of many vision systems. Existing work in the area has mostly addressed scenes that consist of static or quasi-static structures. When...
Anurag Mittal, Nikos Paragios
ACIVS
2009
Springer
13 years 11 months ago
Multiple Human Tracking in High-Density Crowds
Abstract. In this paper, we present a fully automatic approach to multiple human detection and tracking in high density crowds in the presence of extreme occlusion. Human detection...
Irshad Ali, Matthew N. Dailey
ICIP
2006
IEEE
14 years 6 months ago
Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency
This paper proposes to combine spatial and color coherency with the pixel-wise GMM to determine the background model. We first represent each pixel with a hybrid feature vector, w...
Sheng-Yan Yang, Chiou-Ting Hsu
JMM2
2007
148views more  JMM2 2007»
13 years 4 months ago
Object Segmentation Using Background Modelling and Cascaded Change Detection
— The automatic extraction and analysis of visual information is becoming generalised. The first step in this processing chain is usually separating or segmenting the captured v...
Luís Filipe Teixeira, Jaime S. Cardoso, Lu&...