Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data

✍ Scribed by Robert B. Fisher, Yun-Heh Chen-Burger, Daniela Giordano, Lynda Hardman, Fang-Pang Lin (eds.)

• Publisher: Springer International Publishing
• Year: 2016
• Tongue: English
• Leaves: 321
• Series: Intelligent Systems Reference Library 104
• Edition: 1
• Category: Library

✦ Synopsis

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 tracking, fish species recognition and analysis, a large SQL database to record the results and an efficient retrieval mechanism. Novel user interface mechanisms were developed to provide easy access for marine ecologists, who wanted to explore the dataset. The book is a useful resource for system builders, as it gives an overview of the many new methods that were created to build the Fish4Knowledge system in a manner that also allows readers to see how all the components fit together.

✦ Table of Contents

Front Matter....Pages i-xvii
Overview of the Fish4Knowledge Project....Pages 1-17
User Information Needs....Pages 19-30
Supercomputing Resources....Pages 31-39
Marine Video Data Capture and Storage....Pages 41-50
Logical Data Resource Storage....Pages 51-57
Software Architecture with Flexibility for the Data-Intensive Fish4Knowledge Project....Pages 59-71
Fish4Knowledge Database Structure, Creating and Sharing Scientific Data....Pages 73-82
Intelligent Workflow Management for Fish4Knowledge Using the SWELL System....Pages 83-101
Fish Detection....Pages 103-122
Fish Tracking....Pages 123-139
Hierarchical Classification System with Reject Option for Live Fish Recognition....Pages 141-159
Fish Behavior Analysis....Pages 161-179
Understanding Uncertainty Issues in the Exploration of Fish Counts....Pages 181-205
Data Groundtruthing and Crowdsourcing....Pages 207-227
Counting on Uncertainty: Obtaining Fish Counts from Machine Learning Decisions....Pages 229-238
Experiments with the Full Fish4Knowledge Dataset....Pages 239-259
The Fish4Knowledge Virtual World Gallery....Pages 261-267
Conclusions....Pages 269-281
Back Matter....Pages 283-319

✦ Subjects

Computational Intelligence; Artificial Intelligence (incl. Robotics); Fish & Wildlife Biology & Management