Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data

This book gives a start-to-finish overview of the whole Fish4Knowledge project, in 18 short chapters, each describing one aspect of the project. The Fish4Knowledge project explored the possibilities of big video data, in this case from undersea video. Recording and analyzing 90 thousand hours of video from ten camera locations, the project gives a 3 year view of fish abundance in several tropical coral reefs off the coast of Taiwan. The research system built a remote recording network, over 100 Tb of storage, supercomputer processing, video target detection and

Long-term underwater camera surveillance for monitoring and analysis of fish populations

Long-term monitoring of the underwater environment is still labour intensive work. Using underwater surveillance cameras to monitor this environment has the potential advantage to make the task become less labour intensive. Also, the obtained data can be stored making the research reproducible. In this work, a system to analyse long-term underwater camera footage (more than 3 years of 12 hours a day underwater camera footage from 10 cameras) is described. This system uses video processing software to detect and recognise fish species. This footage is processed on supercomputers, which allow marine biologists to request automatic processing on these videos and afterwards analyse the results using a web-interface that allows them to display counts of fish species in the camera footage

A Video Processing and Data Retrieval Framework for Fish Population Monitoring

In this work we present a framework for fish population monitoring through the analysis of underwater videos. We specifically focus on the user information needs, and on the dynamic data extraction and retrieval mechanisms that support them. Sophisticated though a software tool may be, it is ultimately important that its interface satisfies users' actual needs and that users can easily focus on the specific data of interest. In the case of fish population monitoring, marine biologists have to interact with a system which not only provides information from a biological point of view, but also offers instruments to let them guide the video processing task for both video and algorithm selection. This paper aims at describing the system's underlying video processing and workflow low-level details, and their connection to the user interface for on-demand data retrieval by biologists

A video processing and data retrieval framework for fish population monitoring

htmlabstractIn this work we present a framework for fish population monitoring through the analysis of underwater videos. We specifically focus on the user information needs, and on the dynamic data extraction and retrieval mechanisms that support them. Sophisticated though a software tool may be, it is ultimately important that its interface satisfies users' actual needs and that users can easily focus on the specific data of interest. In the case of fish population monitoring, marine biologists have to interact with a system which not only provides information from a biological point of view, but also offers instruments to let them guide the video processing task for both video and algorithm selection. This paper aims at describing the system's underlying video processing and workflow low-level details, and their connection to the user interface for on-demand data retrieval by biologists

CES-515 Towards Localization and Mapping of Autonomous Underwater Vehicles: A Survey

Autonomous Underwater Vehicles (AUVs) have been used for a huge number of tasks ranging from commercial, military and research areas etc, while the fundamental function of a successful AUV is its localization and mapping ability. This report aims to review the relevant elements of localization and mapping for AUVs. First, a brief introduction of the concept and the historical development of AUVs is given; then a relatively detailed description of the sensor system used for AUV navigation is provided. As the main part of the report, a comprehensive investigation of the simultaneous localization and mapping (SLAM) for AUVs are conducted, including its application examples. Finally a brief conclusion is summarized

Fish tracking using detection in Aquaculture: A Pilot Study

Use two different detection models and combine them with a tracking algorithm to be able to track fish that can be used in further fish welfare applications.Use two different detection models and combine them with a tracking algorithm to be able to track fish that can be used in further fish welfare applications

Ecosystem Monitoring and Port Surveillance Systems

International audienceIn this project, we should build up a novel system able to perform a sustainable and long term monitoring coastal marine ecosystems and enhance port surveillance capability. The outcomes will be based on the analysis, classification and the fusion of a variety of heterogeneous data collected using different sensors (hydrophones, sonars, various camera types, etc). This manuscript introduces the identified approaches and the system structure. In addition, it focuses on developed techniques and concepts to deal with several problems related to our project. The new system will address the shortcomings of traditional approaches based on measuring environmental parameters which are expensive and fail to provide adequate large-scale monitoring. More efficient monitoring will also enable improved analysis of climate change, and provide knowledge informing the civil authority's economic relationship with its coastal marine ecosystems

Tracking the Fine Scale Movements of Fish using Autonomous Maritime Robotics: A Systematic State of the Art Review

This paper provides a systematic state of the art review on tracking the fine scale movements of fish with the use of autonomous maritime robotics. Knowledge of migration patterns and the localization of specific species of fish at a given time is vital to many aspects of conservation. This paper reviews these technologies and provides insight into what systems are being used and why. The review results show that a larger amount of complex systems that use a deep learning techniques are used over more simplistic approaches to the design. Most results found in the study involve Autonomous Underwater Vehicles, which generally require the most complex array of sensors. The results also provide insight into future research such as methods involving swarm intelligence, which has seen an increase in use in recent years. This synthesis of current and future research will be helpful to research teams working to create an autonomous vehicle with intentions to track, navigate or survey

Bearing Based Low Cost Underwater Acoustic Positioning System

The Ocean Robotics turned into one of the major fields of research since the exploration of oceans brings many benefits to the human condition. Remotely operated vehicles (ROVs) and Autonomous Surface Vehicles (ASVs) are the common instruments used in this medium, since they prevent human losses and enable more and reliable data for the projects they are inserted in. Most scenarios include support vehicles such as ASVs for monitoring purposes since they are able to use specialized positioning systems such as Global Positioning System (GPS), which are ineffective in underwater environments. This is due to electromagnetic signals used by GPS being attenuated by the medium. As an alternative, acoustic solutions are used. Underwater Acoustic Positioning Systems (UAPSs) have always been an important field of study being used in multiple marine applications. Acoustic fish tracking allows for behavioural and in-situ fish population studies. This process usually involves tagging fishes with acoustic emitters (i.e. tags) and the usage of acoustic receivers. Robotic autonomous vehicles can then be used to carry the acoustic receivers in order to dynamically cover a greater mission area, improving the efficiency of the localization of acoustic sources. An acoustic tag detector was developed to have real-time detection and identification of acoustic signals. A Direction of Arrival (DoA) algorithm was developed from ground up to enable tracking applications. This dissertation presents the improved results of this new system as well as the tests that were made to the DoA algorithm in a simulated environment. Additionally, the position estimation is improved using a Kalman Filter. This work was developed in the context of the MYTAG Portuguese R&D project, addressing the study and characterization of European flounder migrations and to be applied to any target that has a known acoustic signals. One of the objectives of this project is to eventually use an ASV to track a set of flounders, namely with the ROAZ ASV. The use of an unmanned surface vehicle allows for a non-static baseline. In the proposed solution the acoustic signals are tracked with a system composed of three acoustic receivers that are linked to the same computer using a synchronized time source. Not only that but this solution provides two possible methods for the main objective which is to track targets. These methods enable the possibility to estimate the target’s position in the world, while developing a low-cost solution with a newly developed DoA algorithm