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Using Aspect Graphs to Control the Recovery and Tracking of Deformable Models

机译:使用方面图控制可变形模型的恢复和跟踪

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摘要

Active or deformable models have emerged as a popular modeling paradigm in computer vision. These models have the flexibility to adapt themselves to the image data, offering the potential for both generic object recognition and non-rigid object tracking. Because these active models are underconstrained, however, deformable shape recovery often requires manual segmentation or good model initialization, while active contour trackers have been able to track only an object's translation in the image. In this paper, we report our current progress in using a part-based aspect graph representation of an object14 to provide the missing constraints on data-driven deformable model recovery and tracking processes.
机译:活动或可变形模型已成为计算机视觉中流行的建模范例。这些模型可以灵活地适应图像数据,为通用对象识别和非刚性对象跟踪提供了潜力。但是,由于这些活动模型的约束不足,可变形形状的恢复通常需要手动分割或良好的模型初始化,而活动轮廓跟踪器只能跟踪图像中对象的平移。在本文中,我们报告了我们在使用对象的基于零件的长宽图表示形式以提供数据驱动的可变形模型恢复和跟踪过程中缺少的约束方面的最新进展。

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