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Welcome to the FIBEVID project website

The German Academic Exchange Service (DAAD) funded project FIBEVID (Jan 2016 – Dec 2017) is a joint project of the DCSM department of RheinMain University of Applied Sciences (HSRM, Wiesbaden/Germany) and the National University of Science and Technology (NUST, Islamabad/Pakistan), while the Pakistan Museum of Natural History (PMNH) accompanies the project as an application partner. In FIBEVID underwater computer vision technology is employed for an automated surveying of fish species. The project includes the construction and deployment of suitable underwater camera rigs, as well as the development of innovative software for a semiautomatic localization, tracking, measuring and classification of underwater species. The result of FIBEVID will form the basis for a non-invasive, low-cost surveying of Pakistan’s fish population, and benefit the preservation of endangered species as well as a more sustainable economic exploitation of Pakistan’s resources.

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Contact

Prof. Dr. Adrian Ulges
RheinMain University of Applied Sciences (HSRM)
Unter den Eichen 5, Building C, Room 107
D-65195 Wiesbaden, Germany
Phone: +49-611-9495-1215
Fax: +49-611-9495-1210
E-Mail: Adrian.Ulges(at)hs-rm.de
Prof. Dr. Ulrich Schwanecke
RheinMain University of Applied Sciences (HSRM)
Unter den Eichen 5, Building D, Room 22
D-65195 Wiesbaden, Germany
Phone: +49-611-9495-1254
Fax: +49-611-9495-1240
E-Mail: Ulrich.Schwanecke(at)hs-rm.de
Dr. Faisal Shafait
Director, TUKL-NUST Research & Development Center
Associate Professor, SEECS, National University of Sciences and Technology (NUST)
Phone: +92 51 9085 2064
E-Mail: faisal.shafait(at)seecs.edu.pk
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People

RheinMain University of Applied Sciences (HSRM), Wiesbaden/Germany

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Prof. Dr. Adrian Ulges

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Prof. Dr. Ulrich Schwanecke
National University of Sciences and Technology (NUST), Islamabad/Pakistan

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Prof. Dr.-Ing. Faisal Shafait

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Shoaib Ahmed Siddiqui

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Abdul Hannan Khan

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Syed Hassaan Tauqeer

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Nadja Kurz
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Details

The German Academic Exchange Service (DAAD) funded project FIBEVID (Jan 2016 – Dec 2017) is a joint project of the DCSM department of RheinMain University of Applied Sciences (HSRM, Wiesbaden/Germany) and the National University of Science and Technology (NUST, Islamabad/Pakistan), while the Pakistan Museum of Natural History (PMNH) will accompany the project as an application partner. In FIBEVID underwater computer vision technology will be employed for an automated surveying of fish species. The project includes the construction and deployment of suitable underwater camera rigs, as well as the development of innovative software for a semiautomatic localization, tracking, measuring and classification of underwater species. The result of FIBEVID will form the basis for a non-invasive, low-cost surveying of Pakistan’s fish population, and benefit the preservation of endangered species as well as a more sustainable economic exploitation of Pakistan’s resources.

From a technical perspective, FIBEVID requires a number of tasks, namely (1) the acquisition of ground data describing the identity and basic properties of the targeted fish species, (2) the construction of a camera setup that can be used underwater, as well as the development of several computer vision algorithms for (3) fi sh detection, (4) fi sh tracking, and (5) species recognition. Finally, the technology is to be integrated into a tool, including a user-friendly interface (6).

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Left: A possible camera rig design. Right: The deployment of the camera rig.
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Partners

RheinMain University of Applied Sciences (HSRM)

The department for Design, Computer Science and Media (DCSM) at RheinMain University of Applied Sciences includes a computer science program with about 50 professors and 800 students. One of its research priorities is digital image and video analysis, represented by Prof. Ulrich Schwanecke and Prof. Adrian Ulges. Prof. Schwanecke is a renowned expert in the areas of computer graphics, computer vision, and geometric data processing. Prof. Ulges’ research interests are in video analysis and machine learning. Both have led various computer vision projects: Examples include MTM Auto Code Generator (BMBF ZIM, 2014-16), Optishot (BMBF ZIM, 2013-14) and MOONVID (DFG, 2008-2011). Their joint publication record includes more than 70 research papers, as well as several trade fair exhibits, patents and rewards. Prof. Schwanecke furthermore cooperates with the Alfred-Wegener-Institute (Helmholtz Centre for Polar and Marine Research) in the field of video based fish observation.

 

National University of Sciences and Technology (NUST)

The National University of Sciences and Technology (NUST) is ranked as the #1 university in Pakistan in the category of Engineering and Technology. The NUST team comprises of four researchers. Dr. Faisal Shafait (PI) has extensive experience in computer vision and pattern recognition with over 100 publications to his credit. He has also worked on techniques for identication and measurement of fish using underwater images, providing him with experience relevant to the project. Dr. Asad Butt has worked in computer vision, specifically in multiple-target tracking. His experience with object detection and object tracking will be crucial for the project. Dr. Ahmad Salman is an expert in Machine Learning and will be able to provide valuable input for application of active learning techniques for semi-automatic processing of underwater imagery. Muhammad Imran Malik has experience in image processing systems and will oversee the hardware design components of the system. Dr. Faisal Shafait and Muhammad Imran Malik are alumni of TU Kaiserslautern, Germany. Muhammad Imran Malik was an HEC/DAAD scholar and has joined NUST after submission of his PhD dissertation.

 

Pakistan Museum of Natural History (PMNH)

The Pakistan Museum of Natural History (represented by Deputy Director General, Dr. Mohammad Raque) will accompany the project as an application partner. Its competences include the regular surveying of underwater species on behalf of Pakistan’s authorities. Therefore, PMNH is highly interested in the FIBEVID technology as an environmentally friendly and less cost-intensive alternative. PMNH will provide expertise and ground data regarding its background of fish sampling (locations, range, frequency, current practices) as well as the targeted fish species. Both will serve as valuable input for the development of the recognition tool. Beyond this, PMNH will participate in our field tests.