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Sourav Garg

Sourav Garg

Sourav obtained his Bachelors in Electronics and Communication from Thapar University, India in 2012. After graduating, he worked in the robotics research group of Tata Consultancy Services, an IT company in India for 3 years, where he developed algorithms for robotic applications like human/object tracking, product counting in the retail environment, a tea-serving robot in office environment etc. which was published and presented at various international conferences.

Motivated to delve deeper into robotic vision, Sourav commenced his Ph.D. at QUT in 2015. His thesis title is “Visual Place Recognition under Extreme Viewpoint and Appearance Variations using Semantic, Geometric, and Appearance cues”. His research interests include topics like visual SLAM, visual odometry, visual place recognition and localization, image alignment/registration, and visual semantics. His current research explores ways to exploit visual semantic information and deep-learnt CNNs for visual place recognition and has corresponding publications in RSS, ICRA, IROS, ACRA etc. Sourav’s thesis is supervised by Professor Michael Milford (Principal) and Dr. Niko Suenderhauf (Associate).

Australian Centre for Robotic Vision
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