北京师范大学学报（自然科学版）2017，Vol.53Issue(4)：406-411,6.DOI:10.16360/j.cnki.jbnuns.2017.04.006
一种简单有效的鱼群轨迹追踪算法
A fast and effective algorithm to track fish school
摘要
Abstract
To investigate collective motion of groups of animals,it is important to track multiple individual moving animals and acquire their positions over time and space.A few studies have tried to solve this problem aiming for automated data acquisition.But none have solved the problem adequately,since automated tracking is difficult to achieve due to complexities in individual shape,sophisticated motion patterns and frequent occlusion.Several algorithms on this problem have been published,usually for one special species,the zebra fish,for instance.Such algorithms tended to be very demanding regarding the video quality (high frame rates,high image resolution and steady background),and often are very time-consuming.Here we have developed an integrated approach based on artificial neural networks which enables us to automatically extract individual trajectories from both high and low quality videos.We applied our method to track different fish videos,it was found that our method has a high efficiency and accuracy in most situations.关键词
鱼群运动/多目标追踪/目标检测/数据关联Key words
fish collective behavior/tracking multiple individuals/target detection/data association分类
自科综合引用本文复制引用
张琪,韩战钢..一种简单有效的鱼群轨迹追踪算法[J].北京师范大学学报（自然科学版）,2017,53(4):406-411,6.基金项目
国家自然科学基金资助项目(61374165) （61374165）
