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» Algorithmic Fusion for More Robust Feature Tracking
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FPL
2009
Springer
129views Hardware» more  FPL 2009»
15 years 2 months ago
Self-organizing multi-cue fusion for FPGA-based embedded imaging
Self-organization is a natural concept that helps complex systems to adapt themselves autonomically to their environment. In this paper, we present a self-organizing framework for...
Stefan Wildermann, Gregor Walla, Tobias Ziermann, ...
IVC
2008
135views more  IVC 2008»
14 years 9 months ago
Multi-modal tracking of people using laser scanners and video camera
Inspite extensive research on visual tracking of multiple people in computer vision area, the robustness and usability of visual trackers are still discouraging. Recently, a few l...
Jinshi Cui, Hongbin Zha, Huijing Zhao, Ryosuke Shi...
PAMI
2007
156views more  PAMI 2007»
14 years 9 months ago
Selection and Fusion of Color Models for Image Feature Detection
—The choice of a color model is of great importance for many computer vision algorithms (e.g., feature detection, object recognition, and tracking) as the chosen color model indu...
Harro M. G. Stokman, Theo Gevers
IJCV
2007
134views more  IJCV 2007»
14 years 9 months ago
Multi-sensory and Multi-modal Fusion for Sentient Computing
This paper presents an approach to multi-sensory and multi-modal fusion in which computer vision information obtained from calibrated cameras is integrated with a large-scale sent...
Christopher Town
CVPR
1998
IEEE
15 years 11 months ago
Making Good Features Track Better
This paper addresses robust feature tracking. We extend the well-known Shi-Tomasi-Kanade tracker by introducing an automatic scheme for rejecting spurious features. We employ a si...
Tiziano Tommasini, Andrea Fusiello, Emanuele Trucc...