Active focus and zoom control used for scene analysis

David Bailly, P. Gaussier
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引用次数: 1

Abstract

We propose a visual recognition system for robotic applications in which distance to the visual objects can change a lot (for instance, trying to recognize a distant object learned from a short distance). Our system takes advantage of a single pan-tilt camera controllable in zoom and focus. Focus control allows to detect plans of sharpness in the scene and indirectly to compute a distance. Hence, this information can be used to gain structural information of the visual scene (to segment objects from the ground, to count the number of depth plans in the visual field…) without complex computation. This distance information is then used to control either a software or a hardware zoom to keep the size of the object invariant. The image thus created can be used by view based recognition systems. In a second time we show how by using focus points and neural networks we can improve the detection of sharpness plans in complex scenes. Finally we present a simple method to dynamically control the focus and stabilize it on the plan of sharpness of an object in the scene.
用于场景分析的主动聚焦和变焦控制
我们提出了一种用于机器人应用的视觉识别系统,其中与视觉物体的距离可能会发生很大变化(例如,试图识别从短距离学习的远处物体)。我们的系统利用了一个可控制变焦和对焦的单倾斜相机。对焦控制允许检测场景中的清晰度计划,并间接计算距离。因此,这些信息可以用来获得视觉场景的结构信息(从地面分割物体,计算视野中的深度计划数量……),而不需要复杂的计算。然后使用该距离信息来控制软件或硬件缩放,以保持对象的大小不变。这样创建的图像可以被基于视图的识别系统使用。在第二次,我们展示了如何使用焦点和神经网络,我们可以提高检测的清晰度计划在复杂的场景。最后,我们提出了一种简单的方法来动态控制焦点并使其稳定在场景中物体的清晰度计划上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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