Vision System Programming
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'Howard Moraff', 'PO_EMAI': None, 'PO_PHON': None}
The overall objective of the research is to automate                       the contruction of computer programs for machine vision, thus                   reducing the cost of vision systems, and expanding the scope of                 their applicability to industrial tasks.                                             Automatic vision programming entails two major steps:                      feature selection, and program construction.  The major goal of                 the project is to develop automatic vision programming                          techniques that combine two previously developed feature                        selection techniques construction of a search tree for a given                  task entailing object  recognition and location.                                     The proposed system would semi-automatically generate a                    complete and realistic list of potentially useful object features               and evaluate their effectiveness, identify the best sequence of                 features for a matcher's backtracking search tree, and allow the                programmer to debug and refine the program interactively.
[{'FirstName': 'Robert', 'LastName': 'Bolles', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert C Bolles', 'EmailAddress': None, 'NSF_ID': '000263153', 'StartDate': '06/01/1988', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Prasanna', 'LastName': 'Mulgaonkar', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Prasanna G Mulgaonkar', 'EmailAddress': 'prasann@erg.sri.com', 'NSF_ID': '000241571', 'StartDate': '06/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
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{'Code': '6840', 'Text': 'ROBOTICS'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8713218.xml'}