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Asynchronous Event-Based Binocular Stereo Matching

机译:基于异步事件的双目立体匹配

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We present a novel event-based stereo matching algorithm that exploits the asynchronous visual events from a pair of silicon retinas. Unlike conventional frame-based cameras, recent artificial retinas transmit their outputs as a continuous stream of asynchronous temporal events, in a manner similar to the output cells of the biological retina. Our algorithm uses the timing information carried by this representation in addressing the stereo-matching problem on moving objects. Using the high temporal resolution of the acquired data stream for the dynamic vision sensor, we show that matching on the timing of the visual events provides a new solution to the real-time computation of 3-D objects when combined with geometric constraints using the distance to the epipolar lines. The proposed algorithm is able to filter out incorrect matches and to accurately reconstruct the depth of moving objects despite the low spatial resolution of the sensor. This brief sets up the principles for further event-based vision processing and demonstrates the importance of dynamic information and spike timing in processing asynchronous streams of visual events.
机译:我们提出了一种新颖的基于事件的立体声匹配算法,该算法利用了来自一对硅视网膜的异步视觉事件。与传统的基于帧的相机不同,最近的人工视网膜以类似于生物视网膜的输出单元的方式,将其输出作为异步时间事件的连续流传输。我们的算法使用此表示形式携带的时序信息来解决运动物体上的立体匹配问题。使用动态视觉传感器的已采集数据流的高时间分辨率,我们证明了在视觉事件的时间上进行匹配为结合使用距离的几何约束与3D对象的实时计算提供了新的解决方案到极线。尽管传感器的空间分辨率较低,但所提出的算法能够滤除不正确的匹配并准确地重建运动对象的深度。本简介建立了用于进一步基于事件的视觉处理的原理,并演示了动态信息和峰值定时在处理视觉事件的异步流中的重要性。

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