Pipeline for the 3D Reconstruction of Rigid, Handheld Objects through the Use of Static Cameras

Date
2023-04
Journal Title
Journal ISSN
Volume Title
Publisher
University of the Witwatersrand, Johannesburg
Abstract
In this paper, we develop a pipeline for the 3D reconstruction of handheld objects using a single, static RGB-D camera. We also create a general pipeline to describe the process of handheld object reconstruction. This general pipeline suggests the deconstruction of this task into three main constituents: input, where we decide our main method of data capture; segmentation and tracking, where we identify and track the relevant parts of our captured data; and reconstruction where we develop a method for reconstructing our previous information into 3D models. We successfully create a handheld object reconstruction method using a depth sensor as our input; hand tracking, depth segmentation and optical flow to retrieve relevant information; and reconstruction through the use of ICP and TSDF maps. During this process, we also evaluate other possible variations of this successful method. In one of these variations, we test the effect of using depth-estimation to generate data as- the input to our pipeline. While this experimentation helps us quantify our method’s robustness to noise in the input data, we do conclude that current depth estimation techniques do not provide adequate detail for the reconstruction of handheld objects.
Description
A dissertation submitted in fulfilment of the requirements for the degree of Master of Science (Computer Science), to the Faculty of Science, School of Computer Science & Applied Mathematics, University of the Witwatersrand, Johannesburg, 2023.
Keywords
3D reconstruction, Handheld reconstruction, Object reconstruction, UCTD
Citation
Kambadkone, Saatwik Ramakrishna. (2023). Pipeline for the 3D Reconstruction of Rigid, Handheld Objects through the Use of Static Cameras. [Master's dissertation, University of the Witwatersrand, Johannesburg]. https://hdl.handle.net/10539/41923