Results 211 to 220 of about 175,074 (267)
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Sixth IEEE Workshop on Applications of Computer Vision, 2002. (WACV 2002). Proceedings., 2003
Image sensing is usually done with multiple sensors, like the RGB sensors in color imaging, the IR and EO sensors in surveillance and satellite imaging, etc. The resolution of each sensor can be increased by considering the images of the other sensors, and using the statistical redundancy among the sensors.
Assaf Zomet, Shmuel Peleg
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Image sensing is usually done with multiple sensors, like the RGB sensors in color imaging, the IR and EO sensors in surveillance and satellite imaging, etc. The resolution of each sensor can be increased by considering the images of the other sensors, and using the statistical redundancy among the sensors.
Assaf Zomet, Shmuel Peleg
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Multi-sensor fusion: a perspective
Proceedings., IEEE International Conference on Robotics and Automation, 2002A survey of the state of the art in multisensor fusion is presented. Papers related to fusion have been surveyed and classified into six categories: scene segmentation, representation, 3-D shape, sensor modeling, autonomous robots, and object recognition. A number of fusion strategies have been employed to combine sensor outputs. These strategies range
Hackett, Jay K., Shah, Mubarak
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Multi-sensor location tracking
Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking, 1998ion is appfied to individud events. Hence, the output of the abstraction layer is a set of abstracted events. The represent ation of the output events is free of sensor dependencies. EJI = {E~, .... E.} = {abstrE{), .... abstrE~)} = {abstr(71, T;, L;, 01)),..., abstr(Tn, T;, L;, O;))} = {(T1,L1, 01), ....
Ulf Leonhardt, Jeff Magee
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IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2004
Spatio-triangulation process, based on a multisensor block adjustment, is applied to 40 different VIR and SAR images: Landsat-7 ETM, panchromatic SPOT-4 HRV, multiband ASTER, RADARSAT (fine, standard, wide modes) and ERS-1. The images were acquired over Rocky Mountains, Canada from different view/look angles (nadir, across- and in-track) creating ...
Thierry Toutin +2 more
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Spatio-triangulation process, based on a multisensor block adjustment, is applied to 40 different VIR and SAR images: Landsat-7 ETM, panchromatic SPOT-4 HRV, multiband ASTER, RADARSAT (fine, standard, wide modes) and ERS-1. The images were acquired over Rocky Mountains, Canada from different view/look angles (nadir, across- and in-track) creating ...
Thierry Toutin +2 more
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MULTI-SENSOR FUSION FOR VIDEO SEGMENTATION
International Journal of Pattern Recognition and Artificial Intelligence, 2014Video Segmentation is a fundamental task in computer vision. In many sequences, appearance does not provide enough information to solve the problem. Time-of-Flight cameras provide additional information, namely depth, that can be integrated as an additional feature in a segmentation approach.
Bjxf6rn Scheuermann, Bodo Rosenhahn
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Proceedings of 1st International Conference on Image Processing, 2002
We present a new fusion algorithm based on a non-hierarchical fusion scheme. This new fusion algorithm uses a biologically inspired merging rule to combine multiple arbitrary sized sensor images into a single image without any parameter setting. Features from each individual sensor image are not only well retained in the fused image but also enhanced ...
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We present a new fusion algorithm based on a non-hierarchical fusion scheme. This new fusion algorithm uses a biologically inspired merging rule to combine multiple arbitrary sized sensor images into a single image without any parameter setting. Features from each individual sensor image are not only well retained in the fused image but also enhanced ...
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Generalized Multi-sensor Planning
2006Vision systems for various tasks are increasingly being deployed. Although significant effort has gone into improving the algorithms for such tasks, there has been relatively little work on determining optimal sensor configurations. This paper addresses this need.
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2011
The use of multiple sensors typically requires the fusion of data from different type of sensors. The combined use of such a data has the potential to give an efficient, high quality and reliable estimation. Input data from different sensors allows the introduction of target attributes (target type, size) into the association logic.
Hussain, Dil Muhammad Akbar +2 more
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The use of multiple sensors typically requires the fusion of data from different type of sensors. The combined use of such a data has the potential to give an efficient, high quality and reliable estimation. Input data from different sensors allows the introduction of target attributes (target type, size) into the association logic.
Hussain, Dil Muhammad Akbar +2 more
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2014
In the previous chapters, we have discussed issues concerning hardware, communication and network topologies for the practical deployment of Body Sensor Networks (BSNs). The pursuit of low power miniaturised distributed sensing under a patient’s natural physiological conditions has also imposed significant technical challenges on integrating ...
Guang-Zhong Yang +3 more
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In the previous chapters, we have discussed issues concerning hardware, communication and network topologies for the practical deployment of Body Sensor Networks (BSNs). The pursuit of low power miniaturised distributed sensing under a patient’s natural physiological conditions has also imposed significant technical challenges on integrating ...
Guang-Zhong Yang +3 more
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2018
Low-cost IMU sensors typically show significant amounts of drift and offset. To analyze data from such sensors, additional information is required to compensate for those artefacts. Two main sensor fusion approaches have been proposed: stochastic filtering, often implemented in the form of an extended Kalman filter.
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Low-cost IMU sensors typically show significant amounts of drift and offset. To analyze data from such sensors, additional information is required to compensate for those artefacts. Two main sensor fusion approaches have been proposed: stochastic filtering, often implemented in the form of an extended Kalman filter.
openaire +1 more source