By Robert B. Fisher, Yun-Heh Chen-Burger, Daniela Giordano, Lynda Hardman, Fang-Pang Lin

This publication provides a start-to-finish review of the entire Fish4Knowledge undertaking, in 18 brief chapters, each one describing one point of the undertaking. The Fish4Knowledge undertaking explored the probabilities of huge video facts, for this reason from undersea video. Recording and examining ninety thousand hours of video from ten digicam destinations, the venture supplies a three yr view of fish abundance in different tropical coral reefs off the coast of Taiwan. The study procedure outfitted a distant recording community, over a hundred Tb of garage, supercomputer processing, video objective detection and monitoring, fish species attractiveness and research, a wide SQL database to checklist the implications and an effective retrieval mechanism. Novel person interface mechanisms have been built to supply easy accessibility for marine ecologists, who desired to discover the dataset. The e-book is an invaluable source for approach developers, because it provides an outline of the various new equipment that have been created to construct the Fish4Knowledge procedure in a fashion that still permits readers to determine how the entire parts healthy together.

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5. Exploiting fish, system function and system capability ontologies to convert queries into workflow sequences. 6. Helping marine ecologists explore the fish database, to explore and answer questions about the fish population. Many of the research directions were motivated by interviews with marine ecologists, to help understand their research questions and needs. The key achievements/discoveries/innovations of the project were: 1. Advancing the image analysis technology for video for moving object detection: through development of new methods for background modeling usable in both underwater and standard video, a new covariance particle filter able to handle multi-object occlusions and to track effectively objects with complex and unpredictable 3D trajectories, and a novel approach for discriminating objects of interest from the background, by integrating both objectness and motion properties.

3 Implementation model of job dispatch interface so users can easily submit jobs without knowing the details of the schedulers. A middleware, Job Dispatcher, was designed for F4K developer during experimental stage as a test-bed to submit jobs to the proper system and to track job status. A conceptual diagram of the Job Dispatcher interface is shown in Fig. 3. The rest of this section will describe the design of the interface in detail. 1 Distributed Resource Management System A distributed resource management system is a set of software products that enable distributed computing by providing end-to-end access to computing resources through load sharing and dynamic job scheduling within heterogeneous computing environments.

4 Summary In this chapter, we described briefly two heterogeneous platforms for F4K components to execute compute intensive image processing tasks. A multicore supercomputing platform, Windrider, acted as the main execution platform with 96 cores, several open queues with varying capacities and the LSF resource scheduler. The VM cluster was the alternative platform which utilizes Oracle’s Grid Engine and has the developer’s full capacity in terms of processor usage. The following chapters will demonstrate that both platforms were used effectively for the compute intensive tasks of F4K.

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