Object Extraction and Reconstruction in Active Video

Ye Lu, Ze-Nian Li
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引用次数: 1

Abstract

A new method of video object extraction is proposed to accurately obtain the object of interest from actively acquired videos. Traditional video object extraction techniques often operate under the assumption of homogeneous object motion and extract various parts of the video that are motion consistent as objects. In contrast, the proposed active video object extraction (AVOE) paradigm assumes that the object of interest is being actively tracked by a non-calibrated camera under general motion and classifies the possible movements of the camera that result in the 2D motion patterns as recovered from the image sequence. Consequently, the AVOE method is able to extract the single object of interest from the active video. We formalize the AVOE process using notions from Gestalt psychology. We define a new Gestalt factor called "shift and hold" and present 2D object extraction algorithms. Moreover, since an active video sequence naturally contains multiple views of the object of interest, we demonstrate that these views can be combined to form a single 3D object regardless of whether the object is static or moving in the video.
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活动视频中的目标提取与重构
提出了一种新的视频对象提取方法,从主动获取的视频中准确提取感兴趣的对象。传统的视频对象提取技术往往是在物体运动均匀的假设下,提取视频中运动一致的各个部分作为对象。相比之下,提出的主动视频对象提取(AVOE)范式假设感兴趣的对象在一般运动下由未校准的摄像机主动跟踪,并将导致2D运动模式的摄像机可能的运动分类为从图像序列中恢复的运动。因此,AVOE方法能够从活动视频中提取单个感兴趣的对象。我们使用格式塔心理学的概念形式化AVOE过程。我们定义了一个新的格式塔因子,称为“移动和保持”,并提出了二维对象提取算法。此外,由于活动视频序列自然包含感兴趣对象的多个视图,因此我们证明,无论对象在视频中是静态还是移动,这些视图都可以组合成一个单一的3D对象。
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