Dense Descriptors for Optical Flow Estimation: A Comparative Study
نویسندگان
چکیده
منابع مشابه
Dense Descriptors for Optical Flow Estimation: A Comparative Study
Estimating the displacements of intensity patterns between sequential frames is a very well-studied problem, which is usually referred to as optical flow estimation. The first assumption among many of the methods in the field is the brightness constancy during movements of pixels between frames. This assumption is proven to be not true in general, and therefore, the use of photometric invariant...
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Modern large displacement optical flow algorithms usually use an initialization by either sparse descriptor matching techniques or dense approximate nearest neighbor fields. While the latter have the advantage of being dense, they have the major disadvantage of being very outlier-prone as they are not designed to find the optical flow, but the visually most similar correspondence. In this artic...
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In recent years, interest in motion analysis has increased with advances in processing capabilities. The usual input in a motion analysis system is an image sequence, with a corresponding increase in the amount of processed data. A typical motion problem is to analyze the motion within 2D image data corresponding to a sequence of frames, of a 3D scene. In computer vision a number of techniques ...
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In this paper, we address the topic of estimating two-frame dense optical flow from the monogenic curvature tensor. The monogenic curvature tensor is a novel image model, from which local phases of image structures can be obtained in a multi-scale way. We adapt the combined local and global (CLG) optical flow estimation approach to our framework. In this way, the intensity constraint equation i...
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ژورنال
عنوان ژورنال: Journal of Imaging
سال: 2017
ISSN: 2313-433X
DOI: 10.3390/jimaging3010012