Abstract
Biological water quality monitoring is an emerging technology. The change of water quality can be quickly tested by using the sensitiveness of aquatic organisms to water environmental change. However, how to extract semantics of fish behavior from the video data is the key technical point of achieving water quality testing. On the base of quantifying fish behavioral characteristics, the essay puts forward the semantic descriptive model of fish behavior. By grouping the parameter of the amount and average height of multi-target fish movement and extracting the semantics of each group, the semantic descriptive network of fish behavior characteristics and water quality finally was set up. The experimental data show that the semantic descriptive network can better characterize the water quality in high temperatures. This provides the theoretical base for the applications of biological water quality tests by the behaviors of fish groups.
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Xiao, G., Fan, Wk., Mao, Jf., Cheng, Zb., Hu, Hb. (2015). Semantic Description of Fish Abnormal Behavior Based on the Computer Vision. In: Tan, T., Ruan, Q., Wang, S., Ma, H., Di, K. (eds) Advances in Image and Graphics Technologies. IGTA 2015. Communications in Computer and Information Science, vol 525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47791-5_3
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DOI: https://doi.org/10.1007/978-3-662-47791-5_3
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