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dc.contributor.authorHo, Swee Ngeeen_US
dc.identifier.citationHo, S. N. (2022). Symmetry detection on shapes and objects in 2D images using feature points. Final Year Project (FYP), Nanyang Technological University, Singapore.
dc.description.abstractSymmetry is a worldwide phenomenon that exists in all forms and shapes in the world. It is a crucial part of geometry, nature, and shapes. It helps to organise our world conceptually by creating patterns that we can analyse and study. With the recent resurging interest of computer vision and computer graphics, it is no doubt that the study of the detection of symmetry will be useful in developing new algorithms or refining existing methods. Potential applications like camera tracking and object pose estimation can benefit from the findings of symmetry detection. This project presents an existing method to detect symmetry in an image, by grouping feature points based on their underlying symmetry and characteristics. With the method, the project aims to analyse how symmetry detection is done on the lowest level and evaluate the effectiveness of the detection, also stating the limitations of the current method.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleSymmetry detection on shapes and objects in 2D images using feature pointsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorZheng Jianminen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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