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Detecting and Correcting Errors in Mental Cutting Test Intersections Computed with Blender

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ICGG 2022 - Proceedings of the 20th International Conference on Geometry and Graphics (ICGG 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 146))

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Abstract

Mental Cutting Test is a widely used format to develop or measure the spatial skills of people in various situations, having different purposes. An exercise consists of a 2D projection of a 3D shape and an intersection plane, denoted by a frame. The task is to choose the shape of their intersection from the set of five shapes. In this paper, we investigate a great number of different shapes that are rendered with Blender, containing various errors that change the basic morphological features of the shapes. After a human-based validation process, we developed a post-processing Python script which detects and corrects the issues of the automatically generated intersections.

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References

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Acknowledgement

Supported by the ÚNKP-21-3 new national excellence program of the ministry for innovation and technology from the source of the national research, development and innovation fund.

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Correspondence to Róbert Tóth .

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Tóth, R., Tóth, B., Zichar, M., Fazekas, A., Hoffmann, M. (2023). Detecting and Correcting Errors in Mental Cutting Test Intersections Computed with Blender. In: Cheng, LY. (eds) ICGG 2022 - Proceedings of the 20th International Conference on Geometry and Graphics. ICGG 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-031-13588-0_79

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  • DOI: https://doi.org/10.1007/978-3-031-13588-0_79

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13587-3

  • Online ISBN: 978-3-031-13588-0

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