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Marine Snow Tracking Stereo Imaging System Junsu Jang

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Marine Snow Tracking Stereo Imaging System Junsu Jang Marine Snow Tracking Stereo Imaging System by Junsu Jang B.Sc., Carnegie Mellon University (2018) Submitted to the Program in Media Arts and Sciences, School of Architecture and Planning in partial fulfillment of the requirements for the degree of Master of Science in Media Arts and Sciences at the Massachusetts Institute of Technology September 2020 © Massachusetts Institute of Technology 2020. All rights reserved. Author.............................................................. Program in Media Arts and Sciences August 17th, 2020 Certified by. Joseph A. Paradiso Professor of Media Arts and Sciences Accepted by . Tod Machover Academic Head, Program in Media Arts and Sciences Marine Snow Tracking Stereo Imaging System by Junsu Jang Submitted to the Program in Media Arts and Sciences, School of Architecture and Planning on August 17th, 2020, in partial fulfillment of the requirements for the degree of Master of Science in Media Arts and Sciences Abstract The transport of particles of organic carbon from the ocean’s surface to its bottom plays a key role in the global carbon cycle and carbon sequestration. Quantifying the rate of this Biological Carbon Pump – the size and velocity distribution of falling particles below the mixing layer, for example – is thus of considerable importance. The complexity of this Pump, however, together with systematic biases in available measurement methodologies and vast spatial and temporal undersampling, makes this quantification difficult. In this thesis I set out to design and build a low-cost underwater stereo-imaging system to remotely measure the flux of sinking particles in the mid-ocean. By record- ing time-lapsed images of marine snow falling through the imaging volume over day- to-week timescales, we can estimate both the particle size distributions and, via 3D particle tracking velocimetry, their velocity distributions too. This allows us to di- rectly estimate the net flux. Making the system low-cost and compact enables large- scale observations capable of resolving relevant length and time-scales over which this flux likely varies in the ocean. The hardware design is thus primarily constrained by the target depth, expected particle size distribution, expected sinking rates, deploy- ment duration, and cost. The resulting prototype was then tested in the lab and, computationally, against simulated data in preparation for eventual deployment the Minion platform, a Lagrangian float designed to quantitatively explore the Biological Carbon Pump. An evaluation of the system’s efficacy in estimating particle concen- tration and sinking rate, and ultimately estimate the particle flux, indicates a good match to our target specifications. Thesis Supervisor: Joseph A. Paradiso Professor of Media Arts and Sciences This thesis has been reviewed and approved by the following committee members Joseph A. Paradiso . Professor of Media Arts and Sciences The MIT Media Lab Allan W. Adams. Principal Investigator of the Future Ocean Lab at MIT MIT Comparative Media Studies / Writing Jennifer S. Chow . Education and Program Manager of Open Ocean Initiative The MIT Media Lab Acknowledgments First, I would like to thank my advisor, Allan Adams, who gave me the op- portunity to work on this project. He always prioritized students’ well-being and growth as an academic and as a person. I am deeply grateful that I could have been a part of his mission: to design and build accessible ocean technologies that enable us to tell accurate and impactful stories about the ocean. He also taught us that communication and collaboration with people from different disciplines is the key to solve the problems regarding the ocean. There are too many valuable lessons that I have learned from working with him and the Future Ocean Lab. I hope to take these lessons with me and to spread our mission and values to the people I encounter next. I am grateful for my academic advisor, Joe Paradiso. He took me on when I was having a challenging time at the MIT Media Lab and allowed me to work with Allan on this project. He provided me with insightful comments throughout the project that brought my attention on important details. I appreciate the welcoming atmosphere of Responsive Environments and being a part of such an inspiring group of people. I would also like to thank Jenni Chow, who regularly checked up on my well-being as well as project status throughout the pandemic. Her bright personality as well as resilience inspired me to stay focused and push on despite challenging situations. In addition, her expertise in biological carbon pump helped me understand and tackle the problem at hand. I am lucky to have been a part of the Future Ocean Lab, with whom I could share such a warm camaraderie. Jacob Bernstain provided tremendous help whenever I was stuck with technical problems and would review hardware design with care- ful analysis. I am also thankful for Charlene Xia and Evan Denmark for their supportive, fun and inspiring conversations throughout our academic journey. The members of the Open Ocean Initiatives, Katy Croff Bell, Jenni Chow and Daniel Novy, fueled me with positivity. Although National Geographic and Lindblad expedition to Alaska in 2019 was not intended for this specific project, the experience helped me think more practically about the future deployments. Addi- tionally, the seminars and conversations during afternoon tea expanded my horizon and inspired me to move forward. On a personal note, I could complete this thesis during the pandemic thanks to my housemates in November House: Karla Haiat Sasson, Ayokunle Akinyemi, Haiyan Xu, Carly Nix, and Annelise Rittberg. On top of their generous offer to share personal items and space to enable my experiments in a domestic environment, they have provided so much care and support for my well-being. Finally, I would like to thank my loving family and friends, who believed in me and provided endless support. I could not have come this far without them. Contents 1 Introduction 1 2 Related Works 4 2.1 Sediment Traps . 5 2.2 Geotracers . 6 2.3 Optics . 7 2.4 Imaging . 8 3 Minions 9 3.1 Challenge . 10 3.2 Design Goals . 11 3.3 Particle Flux . 12 4 Single Imaging Optics 13 4.1 Overview . 13 4.2 Effective Focal Length Underwater . 14 4.2.1 Depth of Field and Imaging Volume . 17 4.2.2 Lens . 19 4.2.3 Setup . 20 4.3 Evaluation . 21 5 Stereo Design 25 5.1 Baseline and Disparity . 25 5.2 Depth Error . 28 5.3 Correspondence search area and probability of confusion . 31 5.4 Imaging Volume . 31 5.5 Design Choice and Evaluation . 33 5.6 Stereo Calibration . 35 5.6.1 Setup . 37 5.6.2 Results . 37 6 Light Design 40 6.1 Calculation Setup . 41 6.2 Ray Tracing from the Light Source to the Camera . 42 6.3 Simulation . 47 6.3.1 Projection onto spheres . 47 6.3.2 Results . 51 6.4 Evaluation of optical elements . 56 7 Electrical System 59 7.1 Embedded System . 59 7.1.1 Camera and LED Synchronization . 61 7.1.2 Image compression and retrieval . 64 7.1.3 Mission Programming and Data Retrieval . 65 7.1.4 Peripheral Electronics . 66 7.1.5 Internal Logging . 66 7.1.6 Wireless Communication Underwater . 66 7.2 Circuit . 67 7.2.1 Mainboard . 67 7.2.2 LED Driver . 68 7.2.3 Circuit Isolation and Short Protection . 69 7.3 Power . 70 7.3.1 Power Consumption . 70 7.3.2 Battery Protection . 71 8 Mechanical Design 72 8.1 Housing . 72 8.2 Float-Fluid Interaction . 73 8.2.1 The Motion of the Float . 73 8.2.2 Heat . 78 8.3 Buoyancy . 79 9 Particle Tracking Velocimentry (PTV) 81 9.1 Image pre-processing . 82 9.2 Particle tracking . 83 9.3 3D coordinate Estimation . 83 9.4 Simulation . 84 9.4.1 Bokeh Effect . 85 9.5 Evaluation . 90 9.5.1 Detection . 90 9.5.2 Tracking Error . 92 9.6 Future Work . 96 9.6.1 Further Evaluation . 98 10 Conclusion 101 10.1 Summary . 101 10.2 Discussions and Future Works . 103 10.2.1 Hardware . 103 10.2.2 Software . 105 10.2.3 Beyond Stereo Imaging System . 105 A Circuit Schematic and Layout 107 B Software 112 C Optics Performance Comparison 113 C.1 Camera Lens . 113 C.2 Light Optics . 114 D Bill of Materials 118 List of Figures 1-1 The flowchart of the biological carbon pump. Biological debris includ- ing plankton aggregates, and once dense enough, start to sink. Some gets consumed by marine organisms, but approximately 1% is known to reach the seafloor. The figure is from [1] . .2 2-2 POC is comprised of various forms of biological debris. The third row shows the marine snow, faecal pellets (center row) and carcasses of planktonic organisms. Not many of these particles seem as round as a sphere. The images are from from [2] . 7 3-1 Summary of how Minion floats will be operated in the field and their functionalities[3] . 9 4-1 Photos of the imaging system for testing in air and in water. 14 4-2 A diagram that shows the geometrical relations on computing the ef- fective field of view and working distance. The ray of light travels through three different media. The diagram is exaggerated for visibility. 15 4-3 We built an optical rail to test each camera against a Siemens star calibration target in air and in water. 20 4-4 Images of the Siemens Star calibration target during test underwater. 21 4-5 A graph of contrast as a function of the spatial resolution in air and underwater. The minimum resolution at 20% contrast is noted.
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