Shazmin Aniza Abdul Shukor
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Preferred name
Shazmin Aniza Abdul Shukor
Official Name
Shazmin Aniza, Abdul Shukor
Alternative Name
Shukor, S. A.
Shukor, S. A.A
S. A.A, Shukor
Shukor, Shazmin Aniza Abdul
Abdul Shukor, Shazmin Aniza
Main Affiliation
Pusat Kecemerlangan Kecerdikan Robotik (COFRI)
Scopus Author ID
57214325384
Researcher ID
GSD-2143-2022

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  • Publication
    Modelling small artefact for preservation – a case study of Perlis heritage
    (IOP Publishing, 2023)
    L Gopal
    ;
    Shazmin Aniza Abdul Shukor
    Heritage preservation is essential for preserving historical sites and cultural artefact for future generations. However, they are prone to damages and destructions due to weather conditions and other factors. 3D models and reconstructions can aid in the conservation of historical sites and artefact. LiDAR (light detection and ranging) technology can be utilized to obtain accurate 3D representation of object or area of interest. This project aims to preserve one of the historical artefact in Perlis, Malaysia which is known as ‘Batu Nisan Acheh’ or the Acheh Gravestone by using 3D model and reconstruction. iPhone 13 Pro Max LiDAR scanner is used to collect the raw dataset of the artefact with Scaniverse application. MATLAB is employed for data processing which includes data filtering, noise reduction, downsampling and 3D surface reconstruction. In addition, a GUI application is also developed in enabling users to upload their desired point cloud files and produce its 3D model for future usage. Results show that the accuracy, effectiveness, and usability of heritage preservation initiatives are improved by combining iPhone 13 Pro Max LiDAR scanning with MATLAB processing, which is useful for virtual displays, restoration, and future study.
  • Publication
    Data collection pipeline for big interior registration and modelling using 3D sensor
    (IOP Publishing, 2023)
    F A Ismail
    ;
    Raj Keren Arumai Nathan
    ;
    Shazmin Aniza Abdul Shukor
    ;
    Jalal Johari
    This paper highlights on the analysis of several data collection pipeline for big interior using Structure sensor. Data of big, large interior, collected by 3D sensors such as Structure sensor is very crucial and important as it could be used to develop 3D as-built model, where the model can be utilized for various purposes like maintenance, management as well as renovation work. However, collecting data of big interiors can be challenging as the outcome of the 3D model can be less accurate due to dimensions of the big interior which surpasses the range of the sensor. Thus, there is a need to have a proper planning when collecting 3D data representing big interior, especially rooms with clutter and occlusion due to furniture and equipment. This project concentrates on developing and testing suitable pipeline in collecting data representing big interior using Structure sensor. Three different methods were proposed, tested and analysed, where the interior is modelled using MeshLab. Results show that Method Two, which is wall by wall approach, is the most suitable among the other pipeline proposed. Thus, this method can be utilized by professionals and experts when using 3D sensors like Structure sensor in collecting big, large interior data.
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