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» Further results for ARX models in adaptive tracking
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ICASSP
2009
IEEE
14 years 2 months ago
RLS-weighted Lasso for adaptive estimation of sparse signals
The batch least-absolute shrinkage and selection operator (Lasso) has well-documented merits for estimating sparse signals of interest emerging in various applications, where obse...
Daniele Angelosante, Georgios B. Giannakis
CA
2003
IEEE
14 years 1 months ago
Expressive Gesture Animation Based on Non Parametric Learning of Sensory-Motor Models
This paper presents an efficient method of learning motion control for autonomous animated characters. The method uses a non parametric learning approach which identifies non line...
Sylvie Gibet, Pierre-Francois Marteau
ICC
2007
IEEE
114views Communications» more  ICC 2007»
13 years 11 months ago
Optimizing Throughput with Carrier Sensing Adaptation for IEEE 802.11 Mesh Networks Based on Loss Differentiation
In high density (HD) mesh networks, packet losses can occur due to co-channel interference (asynchronous interference) or collisions (synchronous interference). In this paper, we f...
Hui Ma, Soo Young Shin, Sumit Roy
CVPR
2009
IEEE
1561views Computer Vision» more  CVPR 2009»
15 years 3 months ago
SURFTrac: Efficient Tracking and Continuous Object Recognition using Local Feature Descriptors
We present an efficient algorithm for continuous image recognition and feature descriptor tracking in video which operates by reducing the search space of possible interest poin...
Duy-Nguyen Ta (Georgia Institute of Technology), W...
ICIP
2005
IEEE
14 years 9 months ago
Augmented particle filtering for efficient visual tracking
Visual tracking is one of the key tasks in computer vision. The particle filter algorithm has been extensively used to tackle this problem due to its flexibility. However the conv...
Chunhua Shen, Michael J. Brooks, Anton van den Hen...