Results 241 to 250 of about 208,485 (269)

Multi-sensor Dynamic Image Fusion

2020
Image fusion can be performed on dynamic images along with the static images. Here, static is referred to images captured from the static platform. For example, multi-focus and remote sensing image fusion assumes source images as static. However, in real-time surveillance applications, dynamic image sequences have to be fused.
Gang Xiao, Durga Prasad Bavirisetti, Gang Liu, Xingchen Zhang   +3 more
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Model-based multi-sensor data fusion

Proceedings 1992 IEEE International Conference on Robotics and Automation, 2003
The authors describe an algorithm for implementing a multisensor system in a model-based environment with consideration of the constraints. Based on an environment model, geometric features and constraints are generated from a CAD model database. Sensor models are used to predict sensor response to certain features and to interpret raw sensor data.
W. Wen, H.F. Durrant-Whyte
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A toxonomy of multi-sensor fusion

Journal of Manufacturing Systems, 1992
Abstract This paper develops a taxonomy for multi-sensor fusion and creates a general formulation to describe the process. Using this formulation as a guide, we identify and discuss the following classes of data for sensor fusion: uniquely determined, over determined, under determined, and sequential data.
Ralph Tanner, Nan K. Loh
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Multi-sensor detection and fusion technique

SPIE Proceedings, 2007
A multi-sensor detection and fusion technology is described in this paper. The system consists of inputs from three sensors, Infra Red, Doppler Motion, and Stereo Video. The technique consists of three processing parts corresponding to each sensor data, and a fusion module, which makes the final decision based on the inputs from the three parts. The
Ashish Bhargave, Barry Ambrose, Freddie Lin, Manthos Kazantzidis   +3 more
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Multi-sensor fusion with Bayesian inference

1997
This paper describes the development of a Bayesian framework for multiple graph matching. The study is motivated by the plethora of multi-sensor fusion problems which can be abstracted as multiple graph matching tasks. The study uses as its starting point the Bayesian consistency measure recently developed by Wilson and Hancock.
Mark L. Williams, Richard C. Wilson, Edwin R. Hancock   +2 more
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Multi sensor track fusion performance metrics

2016 24th Signal Processing and Communication Application Conference (SIU), 2016
Track fusion is one of the primary features in command and control systems. Track information of different sensors are combined to have a more accurate result. Criterions and metrics are required to evaluate and compare different fusion methods during development. This paper summarizes some important track fusion metrics.
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Multi-Sensor Information Fusion and Application

Applied Mechanics and Materials, 2014
Technology of multi-sensor information fusion is an emerging discipline and its theories and methods have been applied in many research areas. In this paper, the model and structure of multi-sensor information fusion, major technologies and methods of information fusion, theoretical system of information fusion as well as application of information ...
Ting Gong, Hui Yan
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Multi-Sensor Data Fusion (MSDF)

2017
The Data Fusion Model maintained by the JDL (Joint Directors of Laboratories) Data Fusion Group is the most widely-used method for categorizing data fusion-related functions. This paper discusses the current effort to revise and expand this model to facilitate the cost-effective development, acquisition, integration and operation of multi-sensor/multi ...
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Survey of Multi-sensor Image Fusion

2014
The paper presents multi-sensor image fusion and its relevant framework and technical characteristics. The image fusion is divided into three level fusions: pixel level, feature level and decision level. It mainly discusses the image fusion algorithm at all levels of fusion, and then makes the summary and comparison of these algorithms.
Dingbing Wu, Aolei Yang, Lingling Zhu, Chi Zhang   +3 more
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Multi-Sensor Panorama Fusion and Visualization

2006
The paper describes a general approach for scanning and visualizing panoramic (360◦) indoor scenes. It combines range data acquired by a laser range finder with color pictures acquired by a rotating CCD line camera. The paper describes coordinate systems of both sensors, specifies the fusion of range and color data acquired by both sensors, and reports
K. Scheibe, R. Klette
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