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Control of a camera for active vision: Foveal vision, smooth tracking and saccade

机译:控制摄像机以实现主动视觉:中央凹视觉,平滑跟踪和扫视

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Several characteristics of the human oculomotor system have been suggested to be useful also for active vision mechanisms. Among others, foveal vision and a tracking scheme based on two different modes, called smooth pursuit and saccade have often been postulated or implemented. The purpose of this paper is to formulate a setup in which the benefit of implementing these schemes can be evaluated in a systematic manner, based on control considerations but incorporating image processing constraints. First, the advantage of using foveal vision is evaluated by computing the size of the foveal window which will allow tracking of the largest possible class of signals. By using linear optimal control theory, this problem can be formulated as a one-variable maximization. Second, foveal vision leads naturally to smooth pursuit, defined as the performance that can be achieved by the controller resulting in the optimal size of the foveal window. This controller is relatively simple (i.e., linear, time-invariant) as is to be expected for this control loop. Finally, when smooth pursuit fails a corrective action must be performed to re-center the target on the fovea. Recent results in linear optimal control, provide the necessary tools for addressing this challenging problem in a systematic manner. [References: 30]
机译:已经提出人类动眼系统的一些特征对于主动视觉机制也是有用的。其中,通常假定或实施基于中央凹视觉和基于两种不同模式的平滑跟踪和扫视的跟踪方案。本文的目的是制定一种设置,其中可以基于控制考虑但结合图像处理约束,以系统的方式评估实现这些方案的好处。首先,通过计算中央凹窗口的大小来评估使用中央凹视觉的优势,该大小将允许跟踪最大可能的信号类别。通过使用线性最优控制理论,该问题可以表述为一变量最大化。其次,中央凹视力自然导致平稳的追逐,定义为控制器可实现的性能,从而导致中央凹窗的最佳尺寸。如该控制回路所期望的那样,该控制器相对简单(即,线性,时不变)。最后,当平滑追踪失败时,必须执行纠正措施以使目标重新位于中央凹上。线性最优控制的最新成果为系统地解决这一难题提供了必要的工具。 [参考:30]

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