Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/476662
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dc.contributor.advisorAzrulhizam Shapi’i, Dr.
dc.contributor.authorSanaz Pichak (P74476)
dc.date.accessioned2023-10-06T09:23:31Z-
dc.date.available2023-10-06T09:23:31Z-
dc.date.issued2019-02-20
dc.identifier.otherukmvital:123755
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/476662-
dc.descriptionThe process of 3D reconstruction is a basic problem in Computer Vision. However, recent researches have been successfully addressed by motion capture systems with body worn markers and multiple cameras. To recover 3D reconstruction from fully-body human pose by single camera still remains a challenging problem. For instance, noisy background, variation in human appearance and self-occlusion were among these challenges. This thesis investigated methods of 3D reconstruction from monocular image sequences in dynamic activities such as sports. Six recent methods were selected based on they focused on recovery fully automated system for estimating 3D human pose for 2D joint location. They tried to solve ill-posed problem due to the wide range of possible projections from the same 2D image to 3D space. These researches have been developed the algorithm that be able to achieve this goal especially in complicated poses of sports. To achieve which method has better performance on tennis player’s images, we reviewed and evaluated them. Evaluation of the methods was divided in two sections. First, the theoretical and comparative study of each method was disclosed to identify the technique used, the problems that enquired and the results achieved in their approach. The comparison of each method helps us to narrow the benefits of each method and the state-of-the-art in this field. After that, the advantages and disadvantages of each method were listed. Also, several factors such as accuracy, self-occlusion and so on have been compared amongst these methods. In Second stage, based on the advantages found in the first stage of evaluation, three methods were chosen to be evaluated using specific data set. Initially, the codes of the three methods on PennAction dataset (tennis) were run and the performance of the methods in 3D reconstruction is showed. Then, the methods were tested on a mixed activities sequence from the CMU motion capture database. The novel of this study is evaluation of recent methods based on the accuracy of their performance on the specific dataset of tennis player. Also, we proposed a technique which combining specific advantages of each method to create a more efficient method for 3D reconstruction of 2D sequential images in the context of outdoor activities.,Master of Information Technology
dc.language.isoeng
dc.publisherUKM, Bangi
dc.relationFaculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat
dc.rightsUKM
dc.subjectUniversiti Kebangsaan Malaysia -- Dissertations
dc.subjectDissertations, Academic -- Malaysia
dc.subject3D reconstruction
dc.subjectHuman body
dc.subjectImage
dc.titleComparative study of 3D reconstruction methods of human body from 2D sequential images in sports
dc.typetheses
dc.format.pages85
dc.identifier.barcode005783(2021)(PL2)
Appears in Collections:Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat

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