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Robust Tracking in Weakly Dynamic Scenes

机译:弱动态场景中的稳健跟踪

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Estimating the inter-frame motion of a free-moving camera is important for the reconstruction of large 3-D scene from one or more sequences of frames. This work focuses on scenes with a mixture of dynamic and static elements and proposes an approach to improve tracking in existing 3-D reconstruction algorithms, as well as provide a basis for new types of 3-D reconstructions that are able to construct scenes of moving objects. The main strategy adopted in this work is to group feature points within fixed block-size within the image then to prune groups whose motion deviates from the dominant motions established through majority voting. Our experiments show that the proposed approach performs well in several outdoor dynamic scenes, significantly outperforming typical feature-based and direct pose estimation techniques in footage with moving elements.
机译:估计自由移动相机的帧间运动对于从一个或多个帧序列重建大型3D场景很重要。这项工作着眼于动态和静态元素混合的场景,并提出了一种改进现有3-D重建算法中的跟踪的方法,并为能够构造运动场景的新型3-D重建提供了基础对象。这项工作采用的主要策略是将特征点在图像内固定块大小内分组,然后对运动偏离通过多数表决建立的主导运动的组进行修剪。我们的实验表明,所提出的方法在多个室外动态场景中表现良好,在具有运动元素的镜头中明显优于典型的基于特征和直接姿势估计的技术。

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