MSc Thesis Defense by: Kavan Mehulkumar Dave

Thursday, May 9, 2024 - 10:00

The School of Computer Science is pleased to present…

An IoT-Based Approach of Synthetic Data Generation with Reduced Reality Gap

MSc Thesis Defense by: Kavan Mehulkumar Dave


Date: Thursday, 09 May 2024

Time:  10:00 am

Location: Dillon Hall, room 265


Computer simulation is a powerful technique to create synthetic images for the testing of computer vision algorithms. However, the discrepancies caused by inconsistencies between the simulated environment and the physical world have made the results of algorithms testing with synthetic datasets hardly reliable in real-world applications, which is a phenomenon called the “reality gap”. Among various factors that impact on photo-realism of computer-synthesized outdoor environments, researchers have analyzed the most influential and identified them as geometry, appearance, lighting, physics, environment, camera, and rendering parameters.
This thesis research develops a novel system for the generation of synthetic datasets with a reduced reality gap. In the system, a scene environment is first constructed with the geometry of objects according to real-world data. Information retrieved for the time of a day from the Internet of Things (IoT) is then used by a simulator engine to render images with the actual appearance of objects, physics of shadows and reflections, and rendering parameters, such as camera, lighting, and environmental conditions. Similarity scores between the synthesized and real-world images are finally calculated to evaluate the effectiveness of the proposed system in reducing the reality gap.
Keywords: Computer Vision, Simulation, Synthetic Data, IoT
Thesis Committee:
Internal Reader: Dr. Imran Ahmad           
External Reader: Dr. Mohammed Khalid
Advisor: Dr. Xiaobu Yuan
Chair: Dr. Dan Wu

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