Publication | Closed Access
Real time vergence control
31
Citations
7
References
2003
Year
Unknown Venue
Autocorrelation ImageReal-time ControlEngineeringAdvanced Motion ControlCamera TechnologyImage AnalysisStereo VisionSystems EngineeringComputational ImagingMachine VisionRobot PerceptionVision RoboticsComputer VisionMotion DetectionRobot VisionComputer Stereo VisionEye TrackingRochester RobotProcess ControlRoboticsStereoscopic ProcessingReal Time
Binocular robots whose camera can be independently directed require some mechanism for aiming both cameras at the same world point. The authors describe a mechanism for verging the cameras of the Rochester Robot in real time. The mechanism consists of a discrete control loop driven by an algorithm that estimates a single disparity from the two cameras. Two algorithms for disparity estimation are presented. The first uses the cepstral-transform approach of Y. Yeshuran and E.L. Schwartz (1987), and it is argued that, in this application, the cepstrum is best understood as autocorrelation with an adaptive filter that acts to sharpen peaks in the autocorrelation image. It is also shown that qualitatively similar filters have similar effects, with the limiting case being equivalent to deconvolution. Efficient real-time implementations of the cepstral and deconvolution approaches are described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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