MSc Thesis Defense Announcement of Hardik Sonetta:"Bridging the Simulation-to-Reality Gap: Adapting Simulation Environment for Object Recognition"

Wednesday, May 19, 2021 - 10:00 to 12:00


The School of Computer Science is pleased to present… 

MSc Thesis Defense by: Hardik Yogesh Sonetta 

Date: Wednesday May 19th, 2021 
Time: 10:00 AM to 12:00 PM 
Passcode: If interested in attending this event, contact the Graduate Secretary at


Rapid advancements in object recognition have created a huge demand for labeled datasets for the task of training, testing, and validation of different techniques. Due to the wide range of applications, object models in the datasets need to cover both variations in geometric features and diverse conditions in which sensory inputs are obtained. Also, the need to manually label the object models is cumbersome. As a result, it becomes difficult for researchers to gain access to adequate datasets for the development of new methods or algorithms. In comparison, computer simulation has been considered a cost-effective solution to generate simulated data for the training, testing, and validation of object recognition techniques. However, its effectiveness has been the major concern due to a problem commonly known as the reality gap, which emphasizes the differences that exist between real and simulated images. Aimed at bridging the reality gap, this study first identifies the influential factors that cause the problem and then proposes to adjust the setting of simulation to not only imitate the objects but also the environment that matches with the real-world scenario. In addition, it includes a system structure to retrieve information of the real world and to incorporate this information in the setting of environmental properties in simulation. The proposed approach enables the rendering of realistic data with ground-truth labels, thus making simulated datasets a cost-effective and efficient alternative. 
Keywords: Simulation, Synthetic Dataset, Reality Gap, Object Recognition  

MSc Thesis Committee:

Internal Reader: Dr. Imran Ahmad
External Reader: Dr. Mohammed Khalid
Advisor: Dr. Dan Wu
Co-Advisor: Dr. Xiaobu Yuan
Chair: Dr. Peter Tsin

MSc Thesis Defense Announcement 

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