Model-based recognition and motion tracking depends upon the ability to solve for projection and model parameters that will best fit a 3-D model to matching 2-D image features. This paper extends current methods of parameter solving to handle objects with

Figure3:Twoiterationsofconvergenceareshownfordetermining3-Dviewpointandtheheightofthepyramidfrompartialmatchesto2-Dimagesegments.Perpendicularerrorsbeingminimizedaredisplayedasgraybarsbetweenmodelandimageedges.

thereforesolve rstforthosewithhigherstandarddeviations.Forourproblem,thisimpliesthatconvergencefordif cultproblemswillproceedbysolving rstfortranslationsandthenproceedingonsubsequentiterationstosolveforrotationsand nallyshort-rangeinternalmodelparameters.

6Resultsofimplementation

Allofthemethodsforobjectmodelingandparametersolvingdescribedabovehavebeenim-plementedinabout4000linesofCcode.Averysimpleexampleofmodel ttingisshowninFigure3.Themodelisapyramidwithaninternalparameterallowingforvariableheight.Themodelwasprojectedfromoneparticularsetofparametervalues,andrandomintervalsofsome

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