Abstract
In recent times computer recognition has become most powerful tool for many robotic applications. Applications like inspection, surveillance, industrial automation and gaming needs 3D positional data in order to interact with external environment and this can be achieved by computer recognition. Computer recognition can be done by using many different tools which are OpenCV, Matlab, OpenGL, etc. OpenCV has an optimized library with 500 useful functions for detecting, tracking, image transformation, 3D vision, etc. The scope of this project is to get 3D position of an object from two sensors. The sensors are two cameras which are needed to be calibrated before they see the 3D object. Calibration is the process in which the output image from two cameras is vertically aligned, which means all pixel points are vertically aligned. After calibration these two images from camera1 and camera 2 are inputted into openCV 3D function. This application is majorly designed for Ping Pong game shooter. The coding part of this project includes writing code in C++ using OpenCV libraries for calibrating cameras, and recognition for tracking 3D object. The output of the coding part is to get 3D position of player’s bat from cameras in camera coordinate system. This 3D positional data can be inputted into the shooter so that shooter’s joints can move automatically to shoot the ball exactly to the player’s bat for training purposes. This 3D vision technology can be used in many other applications like industrial robots, unmanned vehicles, intelligent surveillance, medical devices, gaming, etc.