Hierarchical Method for Stereophotogrammetric Multi-object-Position Measurement
The classical stereophotogrammetric methods based on area correlation are relatively slow if the whole image is analyzed. The new proposed method differs from classical stereophotogrammetric methods in that a hierarchical structure is incorporated in the procedure, so that real-time processing is po...
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| creator | Tornow, M. Michaelis, B. Kuhn, R. W. Calow, R. Mecke, R. |
| description | The classical stereophotogrammetric methods based on area correlation are relatively slow if the whole image is analyzed. The new proposed method differs from classical stereophotogrammetric methods in that a hierarchical structure is incorporated in the procedure, so that real-time processing is possible and the relative error is kept reasonably constant even with large variations in one direction (e.g. in road traffic analysis). This is achieved by adapting image resolution to distance. Computation costs are significantly reduced. The method is very suited for implementation in hardware; it runs in real time and can be applied to moving objects that are automatically segmented. The aim of this research project is to reduce the computation power needed although a complex quality criterion is used. |
| doi_str_mv | 10.1007/978-3-540-45243-0_22 |
| format | Book Chapter |
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The aim of this research project is to reduce the computation power needed although a complex quality criterion is used.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Cross Correlation Function</subject><subject>Epipolar Line</subject><subject>Exact sciences and technology</subject><subject>Hardware Implementation</subject><subject>Intelligent Vehicle</subject><subject>Pattern recognition. Digital image processing. 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The new proposed method differs from classical stereophotogrammetric methods in that a hierarchical structure is incorporated in the procedure, so that real-time processing is possible and the relative error is kept reasonably constant even with large variations in one direction (e.g. in road traffic analysis). This is achieved by adapting image resolution to distance. Computation costs are significantly reduced. The method is very suited for implementation in hardware; it runs in real time and can be applied to moving objects that are automatically segmented. The aim of this research project is to reduce the computation power needed although a complex quality criterion is used.</abstract><cop>Germany</cop><pub>Springer Berlin / Heidelberg</pub><doi>10.1007/978-3-540-45243-0_22</doi><oclcid>934981740</oclcid><tpages>8</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Lecture notes in computer science, 2003, Vol.2781, p.164-171 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_15552150 |
| source | Springer Books |
| subjects | Applied sciences Artificial intelligence Computer science control theory systems Cross Correlation Function Epipolar Line Exact sciences and technology Hardware Implementation Intelligent Vehicle Pattern recognition. Digital image processing. Computational geometry Reference Block |
| title | Hierarchical Method for Stereophotogrammetric Multi-object-Position Measurement |
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