Improved Sensors Based on <italic>Scheimpflug</italic> Conditions and Multi-Focal Constraints

Abstract

Binocular vision sensor composed of two traditional camerasis widely utilized in many fields. However, there are still twodeficiencies, i.e. limited measurement area and weakconstraint for feature matching. In this paper, we firstintroduced measurement principle of the Scheimpflug camera and its calibrationmethod. Then an improved binocular vision sensor composed of two Scheimpflug cameras is constructed. Measurement area is maximized.Then, a trinocular vision sensor as an example of the multi-viewstereo vision sensor is analyzed and multi-focal constraint basedmeasurement model is given. Feature matching according to theconstraint of a trifocal tensor is strict, which is verified by relatedexperiments. Calibration procedures for the camera and improved visionsensor are detailed. Experiment results show that measurement area ofour improved vision sensor increases up to 86.2% (when tilted angleis 4°). Root mean square error of distance is0.1070/00 with regard to the measurementarea.

Keywords

• Sensor
• Scheimpflug condition%22%2C%22default_operator%22%3A%22AND%22%7D%7D%7D"> <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">Scheimpflug</italic> condition
• multi-focal constraint
• measurement area