Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems最新文献_第2页

Audio-visual sensor fusion system for intelligent sound sensing 用于智能声音感知的视听传感器融合系统

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398413

Kota Takahashi, Hiro Yamasaki

{"title":"Audio-visual sensor fusion system for intelligent sound sensing","authors":"Kota Takahashi, Hiro Yamasaki","doi":"10.1109/MFI.1994.398413","DOIUrl":"https://doi.org/10.1109/MFI.1994.398413","url":null,"abstract":"An intelligent sensing system is proposed, which extracts a target sound signal autonomously from multi-microphone signals corrupted by interference ambient noise. Although many types of intelligent signal receivers with multiple sensors have been proposed recently, the use of audio-visual sensor fusion techniques is a special feature of the system described here. This sensor fusion system can be divided into two subsystems: an audio subsystem and a visual subsystem. The audio subsystem extracts a target signal with a digital filter composed of tapped delay lines and adjustable weights. These weights are renewed by a special adaptive algorithm, which is called the \"cue signal method\". For adaptation, the cue signal method needs only a narrow bandwidth signal which correlates with the power level of the target signal. This narrow bandwidth signal is called the \"cue signal\". The role of the visual subsystem is, therefore, to generate a cue signal. The authors have already proposed methods for generating a cue signal using video images. Sensor fusion of audio and visual information was accomplished by simple methods. In this paper, two new sensor fusion techniques are proposed. One is a method for generating a cue signal using not only video images but also microphone signals, and the other is a method for generating a cue signal using microphone signals, video images and internal knowledge. Both are a hierarchical sensor fusion of audio and visual information. In order to evaluate and demonstrate the sensor fusion algorithm, a real-time processing system including seventy DSPs was constructed. The architecture of this system is also described.<<ETX>>","PeriodicalId":133630,"journal":{"name":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126415102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

An application of data fusion to landcover classification of remote sensed imagery: a neural network approach 数据融合在遥感影像土地覆盖分类中的应用:一种神经网络方法

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398379

A. Chiuderi, S. Fini, V. Cappellini

引用次数: 9

Filter design methods of multiple model system 多模型系统的滤波器设计方法

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398480

Yan Dong, Zhang Hongyue

引用次数: 0

Improved tracking of maneuvering targets: the use of turn-rate distributions for acceleration modeling 改进机动目标的跟踪:使用加速建模的转换率分布

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398410

J. P. Helferty

引用次数: 43

Accurate navigation via differential GPS and vehicle local sensors 通过差分GPS和车辆本地传感器进行精确导航

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398453

K. Kobayashi, F. Munekata, K. Watanabe

引用次数: 25

Environment recognition for a mobile robot using double ultrasonic sensors and a CCD camera 基于双超声传感器和CCD相机的移动机器人环境识别

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398384

K. Song, Wen-Hui Tang

{"title":"Environment recognition for a mobile robot using double ultrasonic sensors and a CCD camera","authors":"K. Song, Wen-Hui Tang","doi":"10.1109/MFI.1994.398384","DOIUrl":"https://doi.org/10.1109/MFI.1994.398384","url":null,"abstract":"To move efficiently in an unknown or uncertain environment, a mobile robot must take observation from various sensors to provide information for path planning and execution. A sufficient representation of the external world would also be very useful for self-localization. One of the merits of applying multiple sensors to a mobile robot is the enhancement of environment recognition. In this paper, sensory information combined from double ultrasonic sensors and a CCD camera is provided for this purpose. The authors used ultrasonic sensors for distance measurement and a vision system for object boundaries detection. The authors developed an algorithm to eliminate errors due to the beam opening angle of ultrasonic sensors based on a dual transducer design. An extended discrete Kalman filter was used to fuse raw sensory data and reduce the influence of specular reflection of ultrasonic type transducers. Therefore a more reliable representation was obtained for environment recognition. Computer simulation as well as practical experimental results show that this sensory system can provide useful and robust environment recognition for intelligent robotics.<<ETX>>","PeriodicalId":133630,"journal":{"name":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132184327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Data fusion using large multi-agent networks: an analysis of network structure and performance 使用大型多智能体网络的数据融合:网络结构和性能分析

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398466

A. Knoll, J. Meinkoehn

{"title":"Data fusion using large multi-agent networks: an analysis of network structure and performance","authors":"A. Knoll, J. Meinkoehn","doi":"10.1109/MFI.1994.398466","DOIUrl":"https://doi.org/10.1109/MFI.1994.398466","url":null,"abstract":"Concerns the multi-agent paradigm for structuring the data fusion in large networks of information sources. The general goal is the maximisation of the quality of the result at minimum cost. To this end agents compete for scarce resources or they work in parallel. Both the general granularity of the agent society and the competence assigned to each individual agent determine the information flow. The multitude of parameters involved makes it difficult to optimally adapt the network structure to a given class of sensing tasks. We outline possible network structures and present an approach for analysing a number of important parameters characterising the network. The abstraction enables comparison of different structures. The methods for the analysis may be readily refined to evaluate a specific problem. A model of lateral coordination control in proposed as a result. It is based on the notion of negotiated cooperation between pairs of autonomous sensor agents. The cooperation phase is preceded by a bidding scheme to establish logical communication links. The cooperation is modelled on human social behaviour.<<ETX>>","PeriodicalId":133630,"journal":{"name":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122326164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 31

Determining geodesics of a discrete surface 确定一个离散曲面的测地线

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398405

R. Zantout, Y.F. Zheng

引用次数: 4

New hyper-distributed hyper-parallel AI approach based on chaotic bifurcations and synchronizations 基于混沌分岔和同步的超分布式超并行人工智能新方法

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398425

D. Shuai, Y. Watanabe

引用次数: 2

Adaptive sensor integration for mobile robot navigation 移动机器人导航自适应传感器集成

Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems Pub Date : 1994-10-02 DOI: 10.1109/MFI.1994.398469

Cheng-Chih Lin, R. Lal Tummala

引用次数: 4