@article{(Open Science Index):https://publications.waset.org/pdf/11261,
	  title     = {Optical Fish Tracking in Fishways using Neural Networks},
	  author    = {Alvaro Rodriguez and  Maria Bermudez and  Juan R. Rabuñal and  Jeronimo Puertas},
	  country	= {},
	  institution	= {},
	  abstract     = {One of the main issues in Computer Vision is to extract the movement of one or several points or objects of interest in an image or video sequence to conduct any kind of study or control process. Different techniques to solve this problem have been applied in numerous areas such as surveillance systems, analysis of traffic, motion capture, image compression, navigation systems and others, where the specific characteristics of each scenario determine the approximation to the problem. This paper puts forward a Computer Vision based algorithm to analyze fish trajectories in high turbulence conditions in artificial structures called vertical slot fishways, designed to allow the upstream migration of fish through obstructions in rivers. The suggested algorithm calculates the position of the fish at every instant starting from images recorded with a camera and using neural networks to execute fish detection on images. Different laboratory tests have been carried out in a full scale fishway model and with living fishes, allowing the reconstruction of the fish trajectory and the measurement of velocities and accelerations of the fish. These data can provide useful information to design more effective vertical slot fishways.
},
	    journal   = {International Journal of Environmental and Ecological Engineering},
	  volume    = {4},
	  number    = {8},
	  year      = {2010},
	  pages     = {339 - 345},
	  ee        = {https://publications.waset.org/pdf/11261},
	  url   	= {https://publications.waset.org/vol/44},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 44, 2010},
	}