Fast 3D Reconstruction of Human Figures in Motion

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Creator: 

Nasir, Tashia

Date: 

2018

Abstract: 

We developed a scheme for the dynamic volumetric 3D reconstruction of human figures. We aimed at achieving three key objectives that were accuracy, real-time acquisition of partial view 3D data followed by fast processing of data to produce a complete 3D model, and cost-effectiveness of the process. The research problems we encountered were the selection of appropriate camera technology and capturing environment to carry out the reconstruction. We designed a setup that consisted of multiple depth cameras placed around the object of interest at a fixed distance. We proposed and implemented a complete methodology where the reconstruction was accurate and fast conforming to our research goals. We also analyzed the effect of initial orientation and overlap between multiple partial view 3D scans on the accuracy of the final reconstruction. We achieved the minimum error percentage of 4.67% in our final reconstructed 3D model.

Subject: 

Computer Science

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Master of Applied Science: 
M.App.Sc.

Thesis Degree Level: 

Master's

Thesis Degree Discipline: 

Engineering, Human-Computer Interaction

Parent Collection: 

Theses and Dissertations

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