Abstract
A novel parallel processing approach for computation of Z coordinate based on epipolar geometry of a scene captured with a single camera (monovision) is presented in this paper. The algorithm uses single camera images, before it is used to capture data, the camera is first calibrated. The calibration procedure calculates internal parameters such as distortion coefficient, focal length, and principal point. After the camera’s internal parameters have been defined and set, the image is rectified. The main approach is to retrieve depth information from two or more images of one and the same object or scene. A feature point from one image is mapped to the corresponding feature points on another image. As this process is time-consuming, it is parallelized using OpenMP. A Fundamental matrix is estimated from the corresponding feature points and is calculated based on the epipolar constraint property between two views. Hence intrinsic parameters of camera and matched feature points in space are used to yield Z coordinate by triangulation.
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The work by Rashmi C. was supported by High Performance Computing Project lab, University of Mysore, Mysuru.
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Rashmi, C., Hemantha Kumar, G. (2019). A Parallel Programming Approach for Estimation of Depth in World Coordinate System Using Single Camera. In: Nagabhushan, P., Guru, D., Shekar, B., Kumar, Y. (eds) Data Analytics and Learning. Lecture Notes in Networks and Systems, vol 43. Springer, Singapore. https://doi.org/10.1007/978-981-13-2514-4_7
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DOI: https://doi.org/10.1007/978-981-13-2514-4_7
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