A “Bird's Eye View” (or Surround View) is a popular feature in modern cars and is particularly useful for parking and unparking purposes. This 3D reconstruction of the view uses multiple fisheye cameras and has traditionally been performed by a computer vision-based approach on a fixed mesh. This method is computationally expensive and does not always give ideal results for different types of surroundings. This paper discusses the design and implementation of a Thin-Plate Spline (TPS) algorithm for creating a 3D surround view of the vehicle with configurable vantage points and can be computed efficiently. Furthermore, it can choose from different meshes to adaptively generate a match with different surround-view environments on the fly. By surveying different environments and testing the implementation in a real car, we are able to demonstrate the practical feasibility of our solution 11The video demos of our algorithm have been uploaded to Youtube: https://www.youtube.com/watch?v=-boYsUSA52c, https://www.youtube.com/watch?v=NED435Uj12E. https://www.youtube.com/watch?v=2sZTCIi4X2M&t=2s. Our approach is competitive with the-state-of-the-art 3D reconstruction algorithms in computer vision while having a considerably lower runtime complexity.


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    Title :

    Thin-Plate Spline-based Adaptive 3D Surround View


    Contributors:


    Publication date :

    2019-06-01


    Size :

    1298754 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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