{"title":"Object recognition using a distributed cooperative vision system","authors":"T. Hamada, K. Kamejima","doi":"10.1109/MFI.1994.398387","DOIUrl":null,"url":null,"abstract":"Describes a distributed cooperative method whereby a complicated recognition process is divided into a function based independent recognition algorithm. Each algorithm can determine a certain unknown factor of the object under the condition that some remaining unknown factors are fixed. By introducing a cooperation mechanism, these independent algorithms can be used concurrently to determine all of the unknown factors. This cooperation mechanism is obtained by designing each algorithm as a recursive process which tries to reduce differences between predictive features obtained from a model and the features sensed. This approach results in a vision system that is easily adapted to many applications. A prototype vision system which determines the shape, location, and orientation of objects is developed. Using this system, it is experimentally verified that the proposed method is effective.<<ETX>>","PeriodicalId":133630,"journal":{"name":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MFI.1994.398387","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Describes a distributed cooperative method whereby a complicated recognition process is divided into a function based independent recognition algorithm. Each algorithm can determine a certain unknown factor of the object under the condition that some remaining unknown factors are fixed. By introducing a cooperation mechanism, these independent algorithms can be used concurrently to determine all of the unknown factors. This cooperation mechanism is obtained by designing each algorithm as a recursive process which tries to reduce differences between predictive features obtained from a model and the features sensed. This approach results in a vision system that is easily adapted to many applications. A prototype vision system which determines the shape, location, and orientation of objects is developed. Using this system, it is experimentally verified that the proposed method is effective.<>