Talk Abstract:  Visual input is considered unreliable underwater and therefore its current use in automatic analysis and decisions is limited. This influences the design of autonomous underwater vehicles which are usually equipped with multiple sensors which make them expensive and cumbersome. On the other hand, human divers often manage to complete complicated tasks using a very lean sensor suite that is heavily based on vision. We aim to bridge this gap and develop algorithms that can exploit the problematic visual underwater input, and systems that use this input for underwater tasks. In the talk I will present several methods we developed for enhancing the visibility underwater (published in CVPR 2019, 2022) and ongoing work on underwater autonomous vehicles using vision.

Speaker Biography: Prof. Tali Treibitz is heading the Viseaon marine imaging lab in the School of Marine Sciences in the University of Haifa since 2014. She received the BA degree in computer science and the PhD degree in electrical engineering from the Technion-Israel Institute of Technology in 2001 and 2010, respectively. Between 2010-2013 she has been a post-doctoral researcher in the department of computer science and engineering, in the University of California, San Diego and in the Marine Physical Lab in Scripps Institution of Oceanography. Her lab focuses on cutting edge research in underwater computer vision, scene, color and 3D reconstruction, automatic analysis of scenes, and autonomous decision making based on visual input. Based on the lab’s developments, she established a spin-off company, Seaerra-Vision ltd., that develops technologies for real-time underwater image enhancement.

Lab website: https://www.viseaon.haifa.ac.il/