July 2004
Intermediate to advanced
688 pages
19h 3m
English
Content preview from Emerging Topics in Computer VisionBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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5.7. Conclusion and Future Work
We have presented the current state of the tensor voting framework, which is a product of a number of years of research performed mostly at the University of Southern California. In this section, we present the contributions of the framework to perceptual organization and computer vision problems, as well as the axes of our ongoing and future research.
The tensor voting framework provides a general methodology that can be applied to a large range of problems as long as they can be posed as the inference of salient structures in a metric space of any dimension. The benefits from our representation and voting schemes are that no models need to be known a priori, nor do the data have to fit a parametric model. In ...
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