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Robust visual tracking using a spatio-temporal approach with optical flow

机译:使用具有光流的时空方法强大的视觉跟踪

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Most visual tracking algorithms need more or less features of moving objects such as shape, color, dimension, and speed, etc. A three-dimensional filter based on network resonance has been developed for detection of moving objects with a specific moving velocity. This spatio-temporal approach is able to accomplish tracking tasks for unknown moving objects with overlapped or crossover path. However, constraints of smooth moving trajectory and back ground removal confine its applications. Therefore, this paper incorporates the optical flow technique into the spatio-temporal scheme to overcome those difficulties. Experiments on synthesized images and natural images are conducted to demonstrate improved tracking performance using the proposed method.
机译:大多数视觉跟踪算法需要移动物体的或多或少的移动物体,例如形状,颜色,尺寸和速度等。已经开发了基于网络谐振的三维滤波器,用于检测具有特定移动速度的移动物体。 这种时空方法能够完成具有重叠或交叉路径的未知移动对象的跟踪任务。 然而,平滑移动轨迹和后接地移除的限制限制了其应用。 因此,本文将光学流动技术掺入时空方案中以克服这些困难。 进行了合成图像和自然图像的实验,以展示使用该方法的改进的跟踪性能。

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