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Title: Exploring higher quality point clouds using stereo vision
Authors: Foo, Chuan Ann
Keywords: Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Foo, C. A. (2022). Exploring higher quality point clouds using stereo vision. Final Year Project (FYP), Nanyang Technological University, Singapore.
Project: SCSE21-0683
Abstract: This research investigates the feasibility of creating a useful high-quality point cloud through stereo vision. We will create a homemade stereo camera setup to implement the stereo vision techniques. To generate the point clouds, we will implement traditional stereo vision using our stereo camera setup, PSMNet, and MiDaS, a monocular depth estimate using neural network. We will compare and discuss if stereo vision may provide better depth estimate, and consequently a more accurate representation of the scene in the point cloud, than single camera approaches. Stereo vision with deep learning enhancement will also be explored, such as the state-of-the-art method, PSMNet. A final evaluation will be done to summarise our findings on which method produces the highest quality point cloud that has the least noise as well as the best depth estimate regarding the subject in focus.
Schools: School of Computer Science and Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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