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» A Framework for Implicitly Tracking Data
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ICCV
2007
IEEE
14 years 9 months ago
Robust Visual Tracking Based on Incremental Tensor Subspace Learning
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
SMC
2010
IEEE
148views Control Systems» more  SMC 2010»
13 years 6 months ago
A random finite set based detection and tracking using 3D LIDAR in dynamic environments
—In this paper we describe a fully integrated system for detecting and tracking pedestrians in a dynamic urban environment. The system can reliably detect and track pedestrians t...
Bharath Kalyan, K. W. Lee, W. Sardha Wijesoma, D. ...
ICIP
2007
IEEE
14 years 9 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian
ICCV
2007
IEEE
14 years 9 months ago
Real-time Body Tracking Using a Gaussian Process Latent Variable Model
In this paper, we present a tracking framework for capturing articulated human motions in real-time, without the need for attaching markers onto the subject's body. This is a...
Shaobo Hou, Aphrodite Galata, Fabrice Caillette, N...
MM
2005
ACM
181views Multimedia» more  MM 2005»
14 years 1 months ago
Tracking news stories across different sources
Information linkage is becoming more and more important in this digital age. In this paper, we propose a concept tracking method, which links the news stories with the same topic ...
Yun Zhai, Mubarak Shah