67 resultados para Vision-based row tracking algorithm
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为实现对模型不确定的有约束非线性系统在特定时间域上输出轨迹的有效跟踪,将改进的克隆选择算法用于求解迭代学习控制中的优化问题。提出基于克隆选择算法的非线性优化迭代学习控制。在每次迭代运算后,一个克隆选择算法用于求解下次迭代运算中的最优输入,另一个克隆选择算法用于修正系统参考模型。仿真结果表明,该方法比GA-ILC具有更快的收敛速度,能够有效处理输入上的约束以及模型不确定问题,通过少数几次迭代学习就能取得满意的跟踪效果。
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Chinese Acad Sci, ISCAS Lab Internet Software Technologies
Resumo:
Behavioral and ventilatory parameters have the possibility of predicting the stress state of fish in vivo and in situ. This paper presents a new image-processing algorithm for quantifying the average swimming speed of a fish school in an aquarium. This method is based on the alteration in projected area caused by the movement of individual fish during frame sequences captured at given time intervals. The image enhancement method increases the contrast between fish and background, and is thus suitable for use in turbid aquaculture water. Behavioral parameters (swimming activity and distribution parameters) and changes in ventilation frequency (VF) of tilapia (Oreochromis niloticus) responded to acute fluctuations in dissolved oxygen (DO) which were monitored continuously in the course of normoxia, falling DO level, maintenance of hypoxia (three levels of 1.5, 0.8 and 0.3 mg l(-1)) and subsequent recovery to normoxia. These parameters responded sensitively to acute variations in DO level; they displayed significant changes (P < 0.05) during severe hypoxia (0.8 and 0.3 mg l(-1) level) compared with normoxic condition, but there was no significant difference under conditions of mild hypoxia (1.5 mg l(-1) level). There was no significant difference in VF between two levels of severe hypoxia 0.8 and 0.3 mg l(-1) level during the low DO condition. The activity and distribution parameters displayed distinguishable differences between the 0.8 and 0.3 mg l(-1) levels. The behavioral parameters are thus capable of distinguishing between different degrees of severe hypoxia, though there were relatively large fluctuations. (c) 2006 Elsevier B.V. All rights reserved.
Resumo:
利用双目视觉信息系统实现三维空间中运动物体实时跟踪与测距。当运动目标超出视野范围时,可通过控制摄像机云台转动搜索目标。此外,还研究了在摄像头运动情况下,无需重新标定,即可实现运动物体测距的算法。这里,自适应背景建模法与CamShift算法用于实现运动物体的辨识与跟踪。实验结果证明了所提出的算法能够有效地追踪物体,并同时准确地测量它的三维位置。